diff --git "a/metadata_test.csv" "b/metadata_test.csv"
new file mode 100644--- /dev/null
+++ "b/metadata_test.csv"
@@ -0,0 +1,827 @@
+Chart,Question,Id
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that Naive Bayes algorithm classifies (A,B), as 0.",14400
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that Naive Bayes algorithm classifies (not A, B), as 0.",14401
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that Naive Bayes algorithm classifies (A, not B), as 0.",14402
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that Naive Bayes algorithm classifies (not A, not B), as 0.",14403
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that Naive Bayes algorithm classifies (A,B), as 1.",14404
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that Naive Bayes algorithm classifies (not A, B), as 1.",14405
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that Naive Bayes algorithm classifies (A, not B), as 1.",14406
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that Naive Bayes algorithm classifies (not A, not B), as 1.",14407
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A,B) as 0 for any k ≤ 181.",14408
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, B) as 0 for any k ≤ 181.",14409
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A, not B) as 0 for any k ≤ 181.",14410
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, not B) as 0 for any k ≤ 181.",14411
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A,B) as 1 for any k ≤ 181.",14412
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, B) as 1 for any k ≤ 181.",14413
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A, not B) as 1 for any k ≤ 181.",14414
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, not B) as 1 for any k ≤ 181.",14415
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A,B) as 0 for any k ≤ 72.",14416
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, B) as 0 for any k ≤ 72.",14417
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A, not B) as 0 for any k ≤ 72.",14418
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, not B) as 0 for any k ≤ 72.",14419
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A,B) as 1 for any k ≤ 72.",14420
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, B) as 1 for any k ≤ 72.",14421
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A, not B) as 1 for any k ≤ 72.",14422
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, not B) as 1 for any k ≤ 72.",14423
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A,B) as 0 for any k ≤ 188.",14424
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, B) as 0 for any k ≤ 188.",14425
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A, not B) as 0 for any k ≤ 188.",14426
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, not B) as 0 for any k ≤ 188.",14427
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A,B) as 1 for any k ≤ 188.",14428
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, B) as 1 for any k ≤ 188.",14429
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A, not B) as 1 for any k ≤ 188.",14430
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, not B) as 1 for any k ≤ 188.",14431
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A,B) as 0 for any k ≤ 57.",14432
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, B) as 0 for any k ≤ 57.",14433
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A, not B) as 0 for any k ≤ 57.",14434
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, not B) as 0 for any k ≤ 57.",14435
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A,B) as 1 for any k ≤ 57.",14436
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, B) as 1 for any k ≤ 57.",14437
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A, not B) as 1 for any k ≤ 57.",14438
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, not B) as 1 for any k ≤ 57.",14439
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, the Decision Tree presented classifies (A,B) as 0.",14440
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, the Decision Tree presented classifies (not A, B) as 0.",14441
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, the Decision Tree presented classifies (A, not B) as 0.",14442
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, the Decision Tree presented classifies (not A, not B) as 0.",14443
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, the Decision Tree presented classifies (A,B) as 1.",14444
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, the Decision Tree presented classifies (not A, B) as 1.",14445
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, the Decision Tree presented classifies (A, not B) as 1.",14446
+Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, the Decision Tree presented classifies (not A, not B) as 1.",14447
+Titanic_overfitting_mlp.png,We are able to identify the existence of overfitting for MLP models trained longer than 1249 episodes.,14448
+Titanic_overfitting_mlp.png,We are able to identify the existence of overfitting for MLP models trained longer than 1416 episodes.,14449
+Titanic_overfitting_mlp.png,We are able to identify the existence of overfitting for MLP models trained longer than 1245 episodes.,14450
+Titanic_overfitting_mlp.png,We are able to identify the existence of overfitting for MLP models trained longer than 1392 episodes.,14451
+Titanic_overfitting_mlp.png,We are able to identify the existence of overfitting for MLP models trained longer than 1232 episodes.,14452
+Titanic_overfitting_gb.png,We are able to identify the existence of overfitting for gradient boosting models with more than 129 estimators.,14453
+Titanic_overfitting_gb.png,We are able to identify the existence of overfitting for gradient boosting models with more than 105 estimators.,14454
+Titanic_overfitting_gb.png,We are able to identify the existence of overfitting for gradient boosting models with more than 86 estimators.,14455
+Titanic_overfitting_gb.png,We are able to identify the existence of overfitting for gradient boosting models with more than 149 estimators.,14456
+Titanic_overfitting_gb.png,We are able to identify the existence of overfitting for gradient boosting models with more than 59 estimators.,14457
+Titanic_overfitting_rf.png,We are able to identify the existence of overfitting for random forest models with more than 140 estimators.,14458
+Titanic_overfitting_rf.png,We are able to identify the existence of overfitting for random forest models with more than 57 estimators.,14459
+Titanic_overfitting_rf.png,We are able to identify the existence of overfitting for random forest models with more than 112 estimators.,14460
+Titanic_overfitting_rf.png,We are able to identify the existence of overfitting for random forest models with more than 79 estimators.,14461
+Titanic_overfitting_rf.png,We are able to identify the existence of overfitting for random forest models with more than 147 estimators.,14462
+Titanic_overfitting_knn.png,We are able to identify the existence of overfitting for KNN models with less than 2 neighbors.,14463
+Titanic_overfitting_knn.png,We are able to identify the existence of overfitting for KNN models with less than 3 neighbors.,14464
+Titanic_overfitting_knn.png,We are able to identify the existence of overfitting for KNN models with less than 4 neighbors.,14465
+Titanic_overfitting_knn.png,We are able to identify the existence of overfitting for KNN models with less than 5 neighbors.,14466
+Titanic_overfitting_knn.png,We are able to identify the existence of overfitting for KNN models with less than 6 neighbors.,14467
+Titanic_overfitting_decision_tree.png,We are able to identify the existence of overfitting for decision tree models with more than 2 nodes of depth.,14468
+Titanic_overfitting_decision_tree.png,We are able to identify the existence of overfitting for decision tree models with more than 3 nodes of depth.,14469
+Titanic_overfitting_decision_tree.png,We are able to identify the existence of overfitting for decision tree models with more than 4 nodes of depth.,14470
+Titanic_overfitting_decision_tree.png,We are able to identify the existence of overfitting for decision tree models with more than 5 nodes of depth.,14471
+Titanic_overfitting_decision_tree.png,We are able to identify the existence of overfitting for decision tree models with more than 6 nodes of depth.,14472
+Titanic_overfitting_rf.png,The random forests results shown can be explained by the lack of diversity resulting from the number of features considered.,14473
+Titanic_decision_tree.png,The recall for the presented tree is higher than its accuracy.,14474
+Titanic_decision_tree.png,The precision for the presented tree is higher than its accuracy.,14475
+Titanic_decision_tree.png,The specificity for the presented tree is higher than its accuracy.,14476
+Titanic_decision_tree.png,The recall for the presented tree is lower than its accuracy.,14477
+Titanic_decision_tree.png,The precision for the presented tree is lower than its accuracy.,14478
+Titanic_decision_tree.png,The specificity for the presented tree is lower than its accuracy.,14479
+Titanic_decision_tree.png,The accuracy for the presented tree is higher than its recall.,14480
+Titanic_decision_tree.png,The precision for the presented tree is higher than its recall.,14481
+Titanic_decision_tree.png,The specificity for the presented tree is higher than its recall.,14482
+Titanic_decision_tree.png,The accuracy for the presented tree is lower than its recall.,14483
+Titanic_decision_tree.png,The precision for the presented tree is lower than its recall.,14484
+Titanic_decision_tree.png,The specificity for the presented tree is lower than its recall.,14485
+Titanic_decision_tree.png,The accuracy for the presented tree is higher than its precision.,14486
+Titanic_decision_tree.png,The recall for the presented tree is higher than its precision.,14487
+Titanic_decision_tree.png,The specificity for the presented tree is higher than its precision.,14488
+Titanic_decision_tree.png,The accuracy for the presented tree is lower than its precision.,14489
+Titanic_decision_tree.png,The recall for the presented tree is lower than its precision.,14490
+Titanic_decision_tree.png,The specificity for the presented tree is lower than its precision.,14491
+Titanic_decision_tree.png,The accuracy for the presented tree is higher than its specificity.,14492
+Titanic_decision_tree.png,The recall for the presented tree is higher than its specificity.,14493
+Titanic_decision_tree.png,The precision for the presented tree is higher than its specificity.,14494
+Titanic_decision_tree.png,The accuracy for the presented tree is lower than its specificity.,14495
+Titanic_decision_tree.png,The recall for the presented tree is lower than its specificity.,14496
+Titanic_decision_tree.png,The precision for the presented tree is lower than its specificity.,14497
+Titanic_decision_tree.png,The number of False Positives is higher than the number of True Positives for the presented tree.,14498
+Titanic_decision_tree.png,The number of True Negatives is higher than the number of True Positives for the presented tree.,14499
+Titanic_decision_tree.png,The number of False Negatives is higher than the number of True Positives for the presented tree.,14500
+Titanic_decision_tree.png,The number of False Positives is lower than the number of True Positives for the presented tree.,14501
+Titanic_decision_tree.png,The number of True Negatives is lower than the number of True Positives for the presented tree.,14502
+Titanic_decision_tree.png,The number of False Negatives is lower than the number of True Positives for the presented tree.,14503
+Titanic_decision_tree.png,The number of True Positives is higher than the number of False Positives for the presented tree.,14504
+Titanic_decision_tree.png,The number of True Negatives is higher than the number of False Positives for the presented tree.,14505
+Titanic_decision_tree.png,The number of False Negatives is higher than the number of False Positives for the presented tree.,14506
+Titanic_decision_tree.png,The number of True Positives is lower than the number of False Positives for the presented tree.,14507
+Titanic_decision_tree.png,The number of True Negatives is lower than the number of False Positives for the presented tree.,14508
+Titanic_decision_tree.png,The number of False Negatives is lower than the number of False Positives for the presented tree.,14509
+Titanic_decision_tree.png,The number of True Positives is higher than the number of True Negatives for the presented tree.,14510
+Titanic_decision_tree.png,The number of False Positives is higher than the number of True Negatives for the presented tree.,14511
+Titanic_decision_tree.png,The number of False Negatives is higher than the number of True Negatives for the presented tree.,14512
+Titanic_decision_tree.png,The number of True Positives is lower than the number of True Negatives for the presented tree.,14513
+Titanic_decision_tree.png,The number of False Positives is lower than the number of True Negatives for the presented tree.,14514
+Titanic_decision_tree.png,The number of False Negatives is lower than the number of True Negatives for the presented tree.,14515
+Titanic_decision_tree.png,The number of True Positives is higher than the number of False Negatives for the presented tree.,14516
+Titanic_decision_tree.png,The number of False Positives is higher than the number of False Negatives for the presented tree.,14517
+Titanic_decision_tree.png,The number of True Negatives is higher than the number of False Negatives for the presented tree.,14518
+Titanic_decision_tree.png,The number of True Positives is lower than the number of False Negatives for the presented tree.,14519
+Titanic_decision_tree.png,The number of False Positives is lower than the number of False Negatives for the presented tree.,14520
+Titanic_decision_tree.png,The number of True Negatives is lower than the number of False Negatives for the presented tree.,14521
+Titanic_decision_tree.png,The number of True Positives reported in the same tree is 35.,14522
+Titanic_decision_tree.png,The number of False Positives reported in the same tree is 26.,14523
+Titanic_decision_tree.png,The number of True Negatives reported in the same tree is 22.,14524
+Titanic_decision_tree.png,The number of False Negatives reported in the same tree is 25.,14525
+Titanic_decision_tree.png,The number of True Positives reported in the same tree is 50.,14526
+Titanic_decision_tree.png,The number of False Positives reported in the same tree is 15.,14527
+Titanic_decision_tree.png,The number of True Negatives reported in the same tree is 30.,14528
+Titanic_decision_tree.png,The number of False Negatives reported in the same tree is 37.,14529
+Titanic_decision_tree.png,The number of True Positives reported in the same tree is 47.,14530
+Titanic_decision_tree.png,The number of False Positives reported in the same tree is 19.,14531
+Titanic_decision_tree.png,The number of True Negatives reported in the same tree is 40.,14532
+Titanic_decision_tree.png,The number of False Negatives reported in the same tree is 12.,14533
+Titanic_decision_tree.png,The number of True Positives reported in the same tree is 11.,14534
+Titanic_decision_tree.png,The number of False Positives reported in the same tree is 41.,14535
+Titanic_decision_tree.png,The number of True Negatives reported in the same tree is 13.,14536
+Titanic_decision_tree.png,The number of False Negatives reported in the same tree is 36.,14537
+Titanic_decision_tree.png,The number of True Positives reported in the same tree is 18.,14538
+Titanic_decision_tree.png,The number of False Positives reported in the same tree is 16.,14539
+Titanic_decision_tree.png,The number of True Negatives reported in the same tree is 28.,14540
+Titanic_decision_tree.png,The number of False Negatives reported in the same tree is 44.,14541
+Titanic_overfitting_dt_acc_rec.png,The difference between recall and accuracy becomes smaller with the depth due to the overfitting phenomenon.,14542
+Titanic_overfitting_decision_tree.png,The decision tree is in overfitting for depths above 3.,14543
+Titanic_overfitting_decision_tree.png,The decision tree is in overfitting for depths above 4.,14544
+Titanic_overfitting_decision_tree.png,The decision tree is in overfitting for depths above 5.,14545
+Titanic_overfitting_decision_tree.png,The decision tree is in overfitting for depths above 6.,14546
+Titanic_overfitting_decision_tree.png,The decision tree is in overfitting for depths above 7.,14547
+Titanic_overfitting_decision_tree.png,The decision tree is in overfitting for depths above 8.,14548
+Titanic_overfitting_decision_tree.png,The decision tree is in overfitting for depths above 9.,14549
+Titanic_overfitting_decision_tree.png,The decision tree is in overfitting for depths above 10.,14550
+Titanic_overfitting_decision_tree.png,The chart reporting the recall for different trees shows that the model enters in overfitting for models with depth higher than 3.,14551
+Titanic_overfitting_decision_tree.png,The chart reporting the recall for different trees shows that the model enters in overfitting for models with depth higher than 4.,14552
+Titanic_overfitting_decision_tree.png,The chart reporting the recall for different trees shows that the model enters in overfitting for models with depth higher than 5.,14553
+Titanic_overfitting_decision_tree.png,The chart reporting the recall for different trees shows that the model enters in overfitting for models with depth higher than 6.,14554
+Titanic_overfitting_decision_tree.png,The chart reporting the recall for different trees shows that the model enters in overfitting for models with depth higher than 7.,14555
+Titanic_overfitting_decision_tree.png,The chart reporting the recall for different trees shows that the model enters in overfitting for models with depth higher than 8.,14556
+Titanic_overfitting_decision_tree.png,The chart reporting the recall for different trees shows that the model enters in overfitting for models with depth higher than 9.,14557
+Titanic_overfitting_decision_tree.png,The chart reporting the recall for different trees shows that the model enters in overfitting for models with depth higher than 10.,14558
+Titanic_decision_tree.png,The accuracy for the presented tree is higher than 83%.,14559
+Titanic_decision_tree.png,The recall for the presented tree is higher than 82%.,14560
+Titanic_decision_tree.png,The precision for the presented tree is higher than 84%.,14561
+Titanic_decision_tree.png,The specificity for the presented tree is higher than 85%.,14562
+Titanic_decision_tree.png,The accuracy for the presented tree is lower than 62%.,14563
+Titanic_decision_tree.png,The recall for the presented tree is lower than 87%.,14564
+Titanic_decision_tree.png,The precision for the presented tree is lower than 65%.,14565
+Titanic_decision_tree.png,The specificity for the presented tree is lower than 68%.,14566
+Titanic_decision_tree.png,The accuracy for the presented tree is higher than 86%.,14567
+Titanic_decision_tree.png,The recall for the presented tree is higher than 61%.,14568
+Titanic_decision_tree.png,The precision for the presented tree is higher than 81%.,14569
+Titanic_decision_tree.png,The specificity for the presented tree is higher than 67%.,14570
+Titanic_decision_tree.png,The accuracy for the presented tree is lower than 69%.,14571
+Titanic_decision_tree.png,The recall for the presented tree is lower than 88%.,14572
+Titanic_decision_tree.png,The precision for the presented tree is lower than 76%.,14573
+Titanic_decision_tree.png,The specificity for the presented tree is lower than 73%.,14574
+Titanic_decision_tree.png,The accuracy for the presented tree is higher than 60%.,14575
+Titanic_decision_tree.png,The recall for the presented tree is higher than 77%.,14576
+Titanic_decision_tree.png,The precision for the presented tree is higher than 72%.,14577
+Titanic_decision_tree.png,The specificity for the presented tree is higher than 74%.,14578
+Titanic_decision_tree.png,The accuracy for the presented tree is lower than 63%.,14579
+Titanic_decision_tree.png,The recall for the presented tree is lower than 71%.,14580
+Titanic_decision_tree.png,The precision for the presented tree is lower than 79%.,14581
+Titanic_decision_tree.png,The specificity for the presented tree is lower than 75%.,14582
+Titanic_decision_tree.png,The accuracy for the presented tree is higher than 70%.,14583
+Titanic_decision_tree.png,The recall for the presented tree is higher than 64%.,14584
+Titanic_decision_tree.png,The precision for the presented tree is higher than 66%.,14585
+Titanic_decision_tree.png,The specificity for the presented tree is higher than 78%.,14586
+Titanic_decision_tree.png,The accuracy for the presented tree is lower than 89%.,14587
+Titanic_decision_tree.png,The recall for the presented tree is lower than 90%.,14588
+Titanic_decision_tree.png,The precision for the presented tree is lower than 80%.,14589
+Titanic_decision_tree.png,The specificity for the presented tree is lower than 66%.,14590
+Titanic_decision_tree.png,The accuracy for the presented tree is higher than 73%.,14591
+Titanic_decision_tree.png,The recall for the presented tree is higher than 79%.,14592
+Titanic_decision_tree.png,The precision for the presented tree is higher than 62%.,14593
+Titanic_decision_tree.png,The specificity for the presented tree is higher than 82%.,14594
+Titanic_decision_tree.png,The accuracy for the presented tree is lower than 78%.,14595
+Titanic_decision_tree.png,The recall for the presented tree is lower than 64%.,14596
+Titanic_decision_tree.png,The precision for the presented tree is lower than 66%.,14597
+Titanic_decision_tree.png,The specificity for the presented tree is lower than 89%.,14598
+Titanic_overfitting_rf.png,"Results for Random Forests identified as 2, may be explained by its estimators being in underfitting.",14599
+Titanic_overfitting_rf.png,"Results for Random Forests identified as 3, may be explained by its estimators being in underfitting.",14600
+Titanic_overfitting_rf.png,"Results for Random Forests identified as 10, may be explained by its estimators being in underfitting.",14601
+Titanic_overfitting_rf.png,"Results for Random Forests identified as 2, may be explained by its estimators being in overfitting.",14602
+Titanic_overfitting_rf.png,"Results for Random Forests identified as 3, may be explained by its estimators being in overfitting.",14603
+Titanic_overfitting_rf.png,"Results for Random Forests identified as 10, may be explained by its estimators being in overfitting.",14604
+Titanic_overfitting_knn.png,KNN with more than 2 neighbours is in overfitting.,14605
+Titanic_overfitting_knn.png,KNN with less than 2 neighbours is in overfitting.,14606
+Titanic_overfitting_knn.png,KNN with more than 3 neighbours is in overfitting.,14607
+Titanic_overfitting_knn.png,KNN with less than 3 neighbours is in overfitting.,14608
+Titanic_overfitting_knn.png,KNN with more than 4 neighbours is in overfitting.,14609
+Titanic_overfitting_knn.png,KNN with less than 4 neighbours is in overfitting.,14610
+Titanic_overfitting_knn.png,KNN with more than 5 neighbours is in overfitting.,14611
+Titanic_overfitting_knn.png,KNN with less than 5 neighbours is in overfitting.,14612
+Titanic_overfitting_knn.png,KNN with more than 6 neighbours is in overfitting.,14613
+Titanic_overfitting_knn.png,KNN with less than 6 neighbours is in overfitting.,14614
+Titanic_overfitting_knn.png,KNN with more than 7 neighbours is in overfitting.,14615
+Titanic_overfitting_knn.png,KNN with less than 7 neighbours is in overfitting.,14616
+Titanic_overfitting_knn.png,KNN with more than 8 neighbours is in overfitting.,14617
+Titanic_overfitting_knn.png,KNN with less than 8 neighbours is in overfitting.,14618
+Titanic_overfitting_knn.png,KNN with 1 neighbour is in overfitting.,14619
+Titanic_overfitting_knn.png,KNN with 2 neighbour is in overfitting.,14620
+Titanic_overfitting_knn.png,KNN with 3 neighbour is in overfitting.,14621
+Titanic_overfitting_knn.png,KNN with 4 neighbour is in overfitting.,14622
+Titanic_overfitting_knn.png,KNN with 5 neighbour is in overfitting.,14623
+Titanic_overfitting_knn.png,KNN with 6 neighbour is in overfitting.,14624
+Titanic_overfitting_knn.png,KNN with 7 neighbour is in overfitting.,14625
+Titanic_overfitting_knn.png,KNN with 8 neighbour is in overfitting.,14626
+Titanic_overfitting_knn.png,KNN with 9 neighbour is in overfitting.,14627
+Titanic_overfitting_knn.png,KNN with 10 neighbour is in overfitting.,14628
+Titanic_overfitting_knn.png,KNN is in overfitting for k less than 2.,14629
+Titanic_overfitting_knn.png,KNN is in overfitting for k larger than 2.,14630
+Titanic_overfitting_knn.png,KNN is in overfitting for k less than 3.,14631
+Titanic_overfitting_knn.png,KNN is in overfitting for k larger than 3.,14632
+Titanic_overfitting_knn.png,KNN is in overfitting for k less than 4.,14633
+Titanic_overfitting_knn.png,KNN is in overfitting for k larger than 4.,14634
+Titanic_overfitting_knn.png,KNN is in overfitting for k less than 5.,14635
+Titanic_overfitting_knn.png,KNN is in overfitting for k larger than 5.,14636
+Titanic_overfitting_knn.png,KNN is in overfitting for k less than 6.,14637
+Titanic_overfitting_knn.png,KNN is in overfitting for k larger than 6.,14638
+Titanic_overfitting_knn.png,KNN is in overfitting for k less than 7.,14639
+Titanic_overfitting_knn.png,KNN is in overfitting for k larger than 7.,14640
+Titanic_overfitting_knn.png,KNN is in overfitting for k less than 8.,14641
+Titanic_overfitting_knn.png,KNN is in overfitting for k larger than 8.,14642
+Titanic_decision_tree.png,"As reported in the tree, the number of False Positive is smaller than the number of False Negatives.",14643
+Titanic_decision_tree.png,"As reported in the tree, the number of False Positive is bigger than the number of False Negatives.",14644
+Titanic_overfitting_decision_tree.png,"According to the decision tree overfitting chart, the tree with 3 nodes of depth is in overfitting.",14645
+Titanic_overfitting_decision_tree.png,"According to the decision tree overfitting chart, the tree with 4 nodes of depth is in overfitting.",14646
+Titanic_overfitting_decision_tree.png,"According to the decision tree overfitting chart, the tree with 5 nodes of depth is in overfitting.",14647
+Titanic_overfitting_decision_tree.png,"According to the decision tree overfitting chart, the tree with 6 nodes of depth is in overfitting.",14648
+Titanic_overfitting_decision_tree.png,"According to the decision tree overfitting chart, the tree with 7 nodes of depth is in overfitting.",14649
+Titanic_overfitting_decision_tree.png,"According to the decision tree overfitting chart, the tree with 8 nodes of depth is in overfitting.",14650
+Titanic_decision_tree.png,"A smaller tree would be delivered if we would apply post-pruning, accepting an accuracy reduction of 5%.",14651
+Titanic_decision_tree.png,"A smaller tree would be delivered if we would apply post-pruning, accepting an accuracy reduction of 6%.",14652
+Titanic_decision_tree.png,"A smaller tree would be delivered if we would apply post-pruning, accepting an accuracy reduction of 7%.",14653
+Titanic_decision_tree.png,"A smaller tree would be delivered if we would apply post-pruning, accepting an accuracy reduction of 8%.",14654
+Titanic_decision_tree.png,"A smaller tree would be delivered if we would apply post-pruning, accepting an accuracy reduction of 9%.",14655
+Titanic_decision_tree.png,"A smaller tree would be delivered if we would apply post-pruning, accepting an accuracy reduction of 10%.",14656
+Titanic_pca.png,Using the first 2 principal components would imply an error between 5 and 20%.,14657
+Titanic_pca.png,Using the first 3 principal components would imply an error between 5 and 20%.,14658
+Titanic_pca.png,Using the first 4 principal components would imply an error between 5 and 20%.,14659
+Titanic_pca.png,Using the first 2 principal components would imply an error between 10 and 20%.,14660
+Titanic_pca.png,Using the first 3 principal components would imply an error between 10 and 20%.,14661
+Titanic_pca.png,Using the first 4 principal components would imply an error between 10 and 20%.,14662
+Titanic_pca.png,Using the first 2 principal components would imply an error between 15 and 20%.,14663
+Titanic_pca.png,Using the first 3 principal components would imply an error between 15 and 20%.,14664
+Titanic_pca.png,Using the first 4 principal components would imply an error between 15 and 20%.,14665
+Titanic_pca.png,Using the first 2 principal components would imply an error between 5 and 25%.,14666
+Titanic_pca.png,Using the first 3 principal components would imply an error between 5 and 25%.,14667
+Titanic_pca.png,Using the first 4 principal components would imply an error between 5 and 25%.,14668
+Titanic_pca.png,Using the first 2 principal components would imply an error between 10 and 25%.,14669
+Titanic_pca.png,Using the first 3 principal components would imply an error between 10 and 25%.,14670
+Titanic_pca.png,Using the first 4 principal components would imply an error between 10 and 25%.,14671
+Titanic_pca.png,Using the first 2 principal components would imply an error between 15 and 25%.,14672
+Titanic_pca.png,Using the first 3 principal components would imply an error between 15 and 25%.,14673
+Titanic_pca.png,Using the first 4 principal components would imply an error between 15 and 25%.,14674
+Titanic_pca.png,Using the first 2 principal components would imply an error between 5 and 30%.,14675
+Titanic_pca.png,Using the first 3 principal components would imply an error between 5 and 30%.,14676
+Titanic_pca.png,Using the first 4 principal components would imply an error between 5 and 30%.,14677
+Titanic_pca.png,Using the first 2 principal components would imply an error between 10 and 30%.,14678
+Titanic_pca.png,Using the first 3 principal components would imply an error between 10 and 30%.,14679
+Titanic_pca.png,Using the first 4 principal components would imply an error between 10 and 30%.,14680
+Titanic_pca.png,Using the first 2 principal components would imply an error between 15 and 30%.,14681
+Titanic_pca.png,Using the first 3 principal components would imply an error between 15 and 30%.,14682
+Titanic_pca.png,Using the first 4 principal components would imply an error between 15 and 30%.,14683
+Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Age previously than variable Pclass.,14684
+Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable SibSp previously than variable Pclass.,14685
+Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Parch previously than variable Pclass.,14686
+Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Fare previously than variable Pclass.,14687
+Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Pclass previously than variable Age.,14688
+Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable SibSp previously than variable Age.,14689
+Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Parch previously than variable Age.,14690
+Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Fare previously than variable Age.,14691
+Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Pclass previously than variable SibSp.,14692
+Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Age previously than variable SibSp.,14693
+Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Parch previously than variable SibSp.,14694
+Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Fare previously than variable SibSp.,14695
+Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Pclass previously than variable Parch.,14696
+Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Age previously than variable Parch.,14697
+Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable SibSp previously than variable Parch.,14698
+Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Fare previously than variable Parch.,14699
+Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Pclass previously than variable Fare.,14700
+Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Age previously than variable Fare.,14701
+Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable SibSp previously than variable Fare.,14702
+Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Parch previously than variable Fare.,14703
+Titanic_pca.png,The first 2 principal components are enough for explaining half the data variance.,14704
+Titanic_pca.png,The first 3 principal components are enough for explaining half the data variance.,14705
+Titanic_pca.png,The first 4 principal components are enough for explaining half the data variance.,14706
+Titanic_boxplots.png,Scaling this dataset would be mandatory to improve the results with distance-based methods.,14707
+Titanic_correlation_heatmap.png,Removing variable Pclass might improve the training of decision trees .,14708
+Titanic_correlation_heatmap.png,Removing variable Age might improve the training of decision trees .,14709
+Titanic_correlation_heatmap.png,Removing variable SibSp might improve the training of decision trees .,14710
+Titanic_correlation_heatmap.png,Removing variable Parch might improve the training of decision trees .,14711
+Titanic_correlation_heatmap.png,Removing variable Fare might improve the training of decision trees .,14712
+Titanic_histograms.png,"Not knowing the semantics of Pclass variable, dummification could have been a more adequate codification.",14713
+Titanic_histograms.png,"Not knowing the semantics of Sex variable, dummification could have been a more adequate codification.",14714
+Titanic_histograms.png,"Not knowing the semantics of Age variable, dummification could have been a more adequate codification.",14715
+Titanic_histograms.png,"Not knowing the semantics of SibSp variable, dummification could have been a more adequate codification.",14716
+Titanic_histograms.png,"Not knowing the semantics of Parch variable, dummification could have been a more adequate codification.",14717
+Titanic_histograms.png,"Not knowing the semantics of Fare variable, dummification could have been a more adequate codification.",14718
+Titanic_histograms.png,"Not knowing the semantics of Embarked variable, dummification could have been a more adequate codification.",14719
+Titanic_boxplots.png,Normalization of this dataset could not have impact on a KNN classifier.,14720
+Titanic_boxplots.png,"Multiplying ratio and Boolean variables by 100, and variables with a range between 0 and 10 by 10, would have an impact similar to other scaling transformations.",14721
+Titanic_histograms.png,It is better to drop the variable Pclass than removing all records with missing values.,14722
+Titanic_histograms.png,It is better to drop the variable Sex than removing all records with missing values.,14723
+Titanic_histograms.png,It is better to drop the variable Age than removing all records with missing values.,14724
+Titanic_histograms.png,It is better to drop the variable SibSp than removing all records with missing values.,14725
+Titanic_histograms.png,It is better to drop the variable Parch than removing all records with missing values.,14726
+Titanic_histograms.png,It is better to drop the variable Fare than removing all records with missing values.,14727
+Titanic_histograms.png,It is better to drop the variable Embarked than removing all records with missing values.,14728
+Titanic_histograms.png,"Given the usual semantics of Pclass variable, dummification would have been a better codification.",14729
+Titanic_histograms.png,"Given the usual semantics of Sex variable, dummification would have been a better codification.",14730
+Titanic_histograms.png,"Given the usual semantics of Age variable, dummification would have been a better codification.",14731
+Titanic_histograms.png,"Given the usual semantics of SibSp variable, dummification would have been a better codification.",14732
+Titanic_histograms.png,"Given the usual semantics of Parch variable, dummification would have been a better codification.",14733
+Titanic_histograms.png,"Given the usual semantics of Fare variable, dummification would have been a better codification.",14734
+Titanic_histograms.png,"Given the usual semantics of Embarked variable, dummification would have been a better codification.",14735
+Titanic_histograms.png,"Feature generation based on the use of variable Sex wouldn’t be useful, but the use of Pclass seems to be promising.",14736
+Titanic_histograms.png,"Feature generation based on the use of variable Age wouldn’t be useful, but the use of Pclass seems to be promising.",14737
+Titanic_histograms.png,"Feature generation based on the use of variable SibSp wouldn’t be useful, but the use of Pclass seems to be promising.",14738
+Titanic_histograms.png,"Feature generation based on the use of variable Parch wouldn’t be useful, but the use of Pclass seems to be promising.",14739
+Titanic_histograms.png,"Feature generation based on the use of variable Fare wouldn’t be useful, but the use of Pclass seems to be promising.",14740
+Titanic_histograms.png,"Feature generation based on the use of variable Embarked wouldn’t be useful, but the use of Pclass seems to be promising.",14741
+Titanic_histograms.png,"Feature generation based on the use of variable Pclass wouldn’t be useful, but the use of Sex seems to be promising.",14742
+Titanic_histograms.png,"Feature generation based on the use of variable Age wouldn’t be useful, but the use of Sex seems to be promising.",14743
+Titanic_histograms.png,"Feature generation based on the use of variable SibSp wouldn’t be useful, but the use of Sex seems to be promising.",14744
+Titanic_histograms.png,"Feature generation based on the use of variable Parch wouldn’t be useful, but the use of Sex seems to be promising.",14745
+Titanic_histograms.png,"Feature generation based on the use of variable Fare wouldn’t be useful, but the use of Sex seems to be promising.",14746
+Titanic_histograms.png,"Feature generation based on the use of variable Embarked wouldn’t be useful, but the use of Sex seems to be promising.",14747
+Titanic_histograms.png,"Feature generation based on the use of variable Pclass wouldn’t be useful, but the use of Age seems to be promising.",14748
+Titanic_histograms.png,"Feature generation based on the use of variable Sex wouldn’t be useful, but the use of Age seems to be promising.",14749
+Titanic_histograms.png,"Feature generation based on the use of variable SibSp wouldn’t be useful, but the use of Age seems to be promising.",14750
+Titanic_histograms.png,"Feature generation based on the use of variable Parch wouldn’t be useful, but the use of Age seems to be promising.",14751
+Titanic_histograms.png,"Feature generation based on the use of variable Fare wouldn’t be useful, but the use of Age seems to be promising.",14752
+Titanic_histograms.png,"Feature generation based on the use of variable Embarked wouldn’t be useful, but the use of Age seems to be promising.",14753
+Titanic_histograms.png,"Feature generation based on the use of variable Pclass wouldn’t be useful, but the use of SibSp seems to be promising.",14754
+Titanic_histograms.png,"Feature generation based on the use of variable Sex wouldn’t be useful, but the use of SibSp seems to be promising.",14755
+Titanic_histograms.png,"Feature generation based on the use of variable Age wouldn’t be useful, but the use of SibSp seems to be promising.",14756
+Titanic_histograms.png,"Feature generation based on the use of variable Parch wouldn’t be useful, but the use of SibSp seems to be promising.",14757
+Titanic_histograms.png,"Feature generation based on the use of variable Fare wouldn’t be useful, but the use of SibSp seems to be promising.",14758
+Titanic_histograms.png,"Feature generation based on the use of variable Embarked wouldn’t be useful, but the use of SibSp seems to be promising.",14759
+Titanic_histograms.png,"Feature generation based on the use of variable Pclass wouldn’t be useful, but the use of Parch seems to be promising.",14760
+Titanic_histograms.png,"Feature generation based on the use of variable Sex wouldn’t be useful, but the use of Parch seems to be promising.",14761
+Titanic_histograms.png,"Feature generation based on the use of variable Age wouldn’t be useful, but the use of Parch seems to be promising.",14762
+Titanic_histograms.png,"Feature generation based on the use of variable SibSp wouldn’t be useful, but the use of Parch seems to be promising.",14763
+Titanic_histograms.png,"Feature generation based on the use of variable Fare wouldn’t be useful, but the use of Parch seems to be promising.",14764
+Titanic_histograms.png,"Feature generation based on the use of variable Embarked wouldn’t be useful, but the use of Parch seems to be promising.",14765
+Titanic_histograms.png,"Feature generation based on the use of variable Pclass wouldn’t be useful, but the use of Fare seems to be promising.",14766
+Titanic_histograms.png,"Feature generation based on the use of variable Sex wouldn’t be useful, but the use of Fare seems to be promising.",14767
+Titanic_histograms.png,"Feature generation based on the use of variable Age wouldn’t be useful, but the use of Fare seems to be promising.",14768
+Titanic_histograms.png,"Feature generation based on the use of variable SibSp wouldn’t be useful, but the use of Fare seems to be promising.",14769
+Titanic_histograms.png,"Feature generation based on the use of variable Parch wouldn’t be useful, but the use of Fare seems to be promising.",14770
+Titanic_histograms.png,"Feature generation based on the use of variable Embarked wouldn’t be useful, but the use of Fare seems to be promising.",14771
+Titanic_histograms.png,"Feature generation based on the use of variable Pclass wouldn’t be useful, but the use of Embarked seems to be promising.",14772
+Titanic_histograms.png,"Feature generation based on the use of variable Sex wouldn’t be useful, but the use of Embarked seems to be promising.",14773
+Titanic_histograms.png,"Feature generation based on the use of variable Age wouldn’t be useful, but the use of Embarked seems to be promising.",14774
+Titanic_histograms.png,"Feature generation based on the use of variable SibSp wouldn’t be useful, but the use of Embarked seems to be promising.",14775
+Titanic_histograms.png,"Feature generation based on the use of variable Parch wouldn’t be useful, but the use of Embarked seems to be promising.",14776
+Titanic_histograms.png,"Feature generation based on the use of variable Fare wouldn’t be useful, but the use of Embarked seems to be promising.",14777
+Titanic_histograms.png,Feature generation based on both variables Sex and Pclass seems to be promising.,14778
+Titanic_histograms.png,Feature generation based on both variables Age and Pclass seems to be promising.,14779
+Titanic_histograms.png,Feature generation based on both variables SibSp and Pclass seems to be promising.,14780
+Titanic_histograms.png,Feature generation based on both variables Parch and Pclass seems to be promising.,14781
+Titanic_histograms.png,Feature generation based on both variables Fare and Pclass seems to be promising.,14782
+Titanic_histograms.png,Feature generation based on both variables Embarked and Pclass seems to be promising.,14783
+Titanic_histograms.png,Feature generation based on both variables Pclass and Sex seems to be promising.,14784
+Titanic_histograms.png,Feature generation based on both variables Age and Sex seems to be promising.,14785
+Titanic_histograms.png,Feature generation based on both variables SibSp and Sex seems to be promising.,14786
+Titanic_histograms.png,Feature generation based on both variables Parch and Sex seems to be promising.,14787
+Titanic_histograms.png,Feature generation based on both variables Fare and Sex seems to be promising.,14788
+Titanic_histograms.png,Feature generation based on both variables Embarked and Sex seems to be promising.,14789
+Titanic_histograms.png,Feature generation based on both variables Pclass and Age seems to be promising.,14790
+Titanic_histograms.png,Feature generation based on both variables Sex and Age seems to be promising.,14791
+Titanic_histograms.png,Feature generation based on both variables SibSp and Age seems to be promising.,14792
+Titanic_histograms.png,Feature generation based on both variables Parch and Age seems to be promising.,14793
+Titanic_histograms.png,Feature generation based on both variables Fare and Age seems to be promising.,14794
+Titanic_histograms.png,Feature generation based on both variables Embarked and Age seems to be promising.,14795
+Titanic_histograms.png,Feature generation based on both variables Pclass and SibSp seems to be promising.,14796
+Titanic_histograms.png,Feature generation based on both variables Sex and SibSp seems to be promising.,14797
+Titanic_histograms.png,Feature generation based on both variables Age and SibSp seems to be promising.,14798
+Titanic_histograms.png,Feature generation based on both variables Parch and SibSp seems to be promising.,14799
+Titanic_histograms.png,Feature generation based on both variables Fare and SibSp seems to be promising.,14800
+Titanic_histograms.png,Feature generation based on both variables Embarked and SibSp seems to be promising.,14801
+Titanic_histograms.png,Feature generation based on both variables Pclass and Parch seems to be promising.,14802
+Titanic_histograms.png,Feature generation based on both variables Sex and Parch seems to be promising.,14803
+Titanic_histograms.png,Feature generation based on both variables Age and Parch seems to be promising.,14804
+Titanic_histograms.png,Feature generation based on both variables SibSp and Parch seems to be promising.,14805
+Titanic_histograms.png,Feature generation based on both variables Fare and Parch seems to be promising.,14806
+Titanic_histograms.png,Feature generation based on both variables Embarked and Parch seems to be promising.,14807
+Titanic_histograms.png,Feature generation based on both variables Pclass and Fare seems to be promising.,14808
+Titanic_histograms.png,Feature generation based on both variables Sex and Fare seems to be promising.,14809
+Titanic_histograms.png,Feature generation based on both variables Age and Fare seems to be promising.,14810
+Titanic_histograms.png,Feature generation based on both variables SibSp and Fare seems to be promising.,14811
+Titanic_histograms.png,Feature generation based on both variables Parch and Fare seems to be promising.,14812
+Titanic_histograms.png,Feature generation based on both variables Embarked and Fare seems to be promising.,14813
+Titanic_histograms.png,Feature generation based on both variables Pclass and Embarked seems to be promising.,14814
+Titanic_histograms.png,Feature generation based on both variables Sex and Embarked seems to be promising.,14815
+Titanic_histograms.png,Feature generation based on both variables Age and Embarked seems to be promising.,14816
+Titanic_histograms.png,Feature generation based on both variables SibSp and Embarked seems to be promising.,14817
+Titanic_histograms.png,Feature generation based on both variables Parch and Embarked seems to be promising.,14818
+Titanic_histograms.png,Feature generation based on both variables Fare and Embarked seems to be promising.,14819
+Titanic_mv.png,There is no reason to believe that discarding records showing missing values is safer than discarding the corresponding variables in this case.,14820
+Titanic_mv.png,Dropping all rows with missing values can lead to a dataset with less than 25% of the original data.,14821
+Titanic_mv.png,Dropping all rows with missing values can lead to a dataset with less than 30% of the original data.,14822
+Titanic_mv.png,Dropping all rows with missing values can lead to a dataset with less than 40% of the original data.,14823
+Titanic_mv.png,Dropping all records with missing values would be better than to drop the variables with missing values.,14824
+Titanic_mv.png,Discarding variables Sex and Pclass would be better than discarding all the records with missing values for those variables.,14825
+Titanic_mv.png,Discarding variables Age and Pclass would be better than discarding all the records with missing values for those variables.,14826
+Titanic_mv.png,Discarding variables SibSp and Pclass would be better than discarding all the records with missing values for those variables.,14827
+Titanic_mv.png,Discarding variables Parch and Pclass would be better than discarding all the records with missing values for those variables.,14828
+Titanic_mv.png,Discarding variables Fare and Pclass would be better than discarding all the records with missing values for those variables.,14829
+Titanic_mv.png,Discarding variables Embarked and Pclass would be better than discarding all the records with missing values for those variables.,14830
+Titanic_mv.png,Discarding variables Pclass and Sex would be better than discarding all the records with missing values for those variables.,14831
+Titanic_mv.png,Discarding variables Age and Sex would be better than discarding all the records with missing values for those variables.,14832
+Titanic_mv.png,Discarding variables SibSp and Sex would be better than discarding all the records with missing values for those variables.,14833
+Titanic_mv.png,Discarding variables Parch and Sex would be better than discarding all the records with missing values for those variables.,14834
+Titanic_mv.png,Discarding variables Fare and Sex would be better than discarding all the records with missing values for those variables.,14835
+Titanic_mv.png,Discarding variables Embarked and Sex would be better than discarding all the records with missing values for those variables.,14836
+Titanic_mv.png,Discarding variables Pclass and Age would be better than discarding all the records with missing values for those variables.,14837
+Titanic_mv.png,Discarding variables Sex and Age would be better than discarding all the records with missing values for those variables.,14838
+Titanic_mv.png,Discarding variables SibSp and Age would be better than discarding all the records with missing values for those variables.,14839
+Titanic_mv.png,Discarding variables Parch and Age would be better than discarding all the records with missing values for those variables.,14840
+Titanic_mv.png,Discarding variables Fare and Age would be better than discarding all the records with missing values for those variables.,14841
+Titanic_mv.png,Discarding variables Embarked and Age would be better than discarding all the records with missing values for those variables.,14842
+Titanic_mv.png,Discarding variables Pclass and SibSp would be better than discarding all the records with missing values for those variables.,14843
+Titanic_mv.png,Discarding variables Sex and SibSp would be better than discarding all the records with missing values for those variables.,14844
+Titanic_mv.png,Discarding variables Age and SibSp would be better than discarding all the records with missing values for those variables.,14845
+Titanic_mv.png,Discarding variables Parch and SibSp would be better than discarding all the records with missing values for those variables.,14846
+Titanic_mv.png,Discarding variables Fare and SibSp would be better than discarding all the records with missing values for those variables.,14847
+Titanic_mv.png,Discarding variables Embarked and SibSp would be better than discarding all the records with missing values for those variables.,14848
+Titanic_mv.png,Discarding variables Pclass and Parch would be better than discarding all the records with missing values for those variables.,14849
+Titanic_mv.png,Discarding variables Sex and Parch would be better than discarding all the records with missing values for those variables.,14850
+Titanic_mv.png,Discarding variables Age and Parch would be better than discarding all the records with missing values for those variables.,14851
+Titanic_mv.png,Discarding variables SibSp and Parch would be better than discarding all the records with missing values for those variables.,14852
+Titanic_mv.png,Discarding variables Fare and Parch would be better than discarding all the records with missing values for those variables.,14853
+Titanic_mv.png,Discarding variables Embarked and Parch would be better than discarding all the records with missing values for those variables.,14854
+Titanic_mv.png,Discarding variables Pclass and Fare would be better than discarding all the records with missing values for those variables.,14855
+Titanic_mv.png,Discarding variables Sex and Fare would be better than discarding all the records with missing values for those variables.,14856
+Titanic_mv.png,Discarding variables Age and Fare would be better than discarding all the records with missing values for those variables.,14857
+Titanic_mv.png,Discarding variables SibSp and Fare would be better than discarding all the records with missing values for those variables.,14858
+Titanic_mv.png,Discarding variables Parch and Fare would be better than discarding all the records with missing values for those variables.,14859
+Titanic_mv.png,Discarding variables Embarked and Fare would be better than discarding all the records with missing values for those variables.,14860
+Titanic_mv.png,Discarding variables Pclass and Embarked would be better than discarding all the records with missing values for those variables.,14861
+Titanic_mv.png,Discarding variables Sex and Embarked would be better than discarding all the records with missing values for those variables.,14862
+Titanic_mv.png,Discarding variables Age and Embarked would be better than discarding all the records with missing values for those variables.,14863
+Titanic_mv.png,Discarding variables SibSp and Embarked would be better than discarding all the records with missing values for those variables.,14864
+Titanic_mv.png,Discarding variables Parch and Embarked would be better than discarding all the records with missing values for those variables.,14865
+Titanic_mv.png,Discarding variables Fare and Embarked would be better than discarding all the records with missing values for those variables.,14866
+Titanic_histograms.png,The variable Pclass can be coded as ordinal without losing information.,14867
+Titanic_histograms.png,The variable Sex can be coded as ordinal without losing information.,14868
+Titanic_histograms.png,The variable Age can be coded as ordinal without losing information.,14869
+Titanic_histograms.png,The variable SibSp can be coded as ordinal without losing information.,14870
+Titanic_histograms.png,The variable Parch can be coded as ordinal without losing information.,14871
+Titanic_histograms.png,The variable Fare can be coded as ordinal without losing information.,14872
+Titanic_histograms.png,The variable Embarked can be coded as ordinal without losing information.,14873
+Titanic_histograms.png,"Considering the common semantics for Pclass variable, dummification would be the most adequate encoding.",14874
+Titanic_histograms.png,"Considering the common semantics for Sex variable, dummification would be the most adequate encoding.",14875
+Titanic_histograms.png,"Considering the common semantics for Age variable, dummification would be the most adequate encoding.",14876
+Titanic_histograms.png,"Considering the common semantics for SibSp variable, dummification would be the most adequate encoding.",14877
+Titanic_histograms.png,"Considering the common semantics for Parch variable, dummification would be the most adequate encoding.",14878
+Titanic_histograms.png,"Considering the common semantics for Fare variable, dummification would be the most adequate encoding.",14879
+Titanic_histograms.png,"Considering the common semantics for Embarked variable, dummification would be the most adequate encoding.",14880
+Titanic_histograms.png,"Considering the common semantics for Sex and Pclass variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14881
+Titanic_histograms.png,"Considering the common semantics for Age and Pclass variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14882
+Titanic_histograms.png,"Considering the common semantics for SibSp and Pclass variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14883
+Titanic_histograms.png,"Considering the common semantics for Parch and Pclass variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14884
+Titanic_histograms.png,"Considering the common semantics for Fare and Pclass variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14885
+Titanic_histograms.png,"Considering the common semantics for Embarked and Pclass variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14886
+Titanic_histograms.png,"Considering the common semantics for Pclass and Sex variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14887
+Titanic_histograms.png,"Considering the common semantics for Age and Sex variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14888
+Titanic_histograms.png,"Considering the common semantics for SibSp and Sex variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14889
+Titanic_histograms.png,"Considering the common semantics for Parch and Sex variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14890
+Titanic_histograms.png,"Considering the common semantics for Fare and Sex variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14891
+Titanic_histograms.png,"Considering the common semantics for Embarked and Sex variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14892
+Titanic_histograms.png,"Considering the common semantics for Pclass and Age variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14893
+Titanic_histograms.png,"Considering the common semantics for Sex and Age variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14894
+Titanic_histograms.png,"Considering the common semantics for SibSp and Age variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14895
+Titanic_histograms.png,"Considering the common semantics for Parch and Age variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14896
+Titanic_histograms.png,"Considering the common semantics for Fare and Age variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14897
+Titanic_histograms.png,"Considering the common semantics for Embarked and Age variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14898
+Titanic_histograms.png,"Considering the common semantics for Pclass and SibSp variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14899
+Titanic_histograms.png,"Considering the common semantics for Sex and SibSp variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14900
+Titanic_histograms.png,"Considering the common semantics for Age and SibSp variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14901
+Titanic_histograms.png,"Considering the common semantics for Parch and SibSp variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14902
+Titanic_histograms.png,"Considering the common semantics for Fare and SibSp variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14903
+Titanic_histograms.png,"Considering the common semantics for Embarked and SibSp variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14904
+Titanic_histograms.png,"Considering the common semantics for Pclass and Parch variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14905
+Titanic_histograms.png,"Considering the common semantics for Sex and Parch variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14906
+Titanic_histograms.png,"Considering the common semantics for Age and Parch variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14907
+Titanic_histograms.png,"Considering the common semantics for SibSp and Parch variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14908
+Titanic_histograms.png,"Considering the common semantics for Fare and Parch variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14909
+Titanic_histograms.png,"Considering the common semantics for Embarked and Parch variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14910
+Titanic_histograms.png,"Considering the common semantics for Pclass and Fare variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14911
+Titanic_histograms.png,"Considering the common semantics for Sex and Fare variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14912
+Titanic_histograms.png,"Considering the common semantics for Age and Fare variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14913
+Titanic_histograms.png,"Considering the common semantics for SibSp and Fare variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14914
+Titanic_histograms.png,"Considering the common semantics for Parch and Fare variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14915
+Titanic_histograms.png,"Considering the common semantics for Embarked and Fare variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14916
+Titanic_histograms.png,"Considering the common semantics for Pclass and Embarked variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14917
+Titanic_histograms.png,"Considering the common semantics for Sex and Embarked variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14918
+Titanic_histograms.png,"Considering the common semantics for Age and Embarked variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14919
+Titanic_histograms.png,"Considering the common semantics for SibSp and Embarked variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14920
+Titanic_histograms.png,"Considering the common semantics for Parch and Embarked variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14921
+Titanic_histograms.png,"Considering the common semantics for Fare and Embarked variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14922
+Titanic_class_histogram.png,Balancing this dataset would be mandatory to improve the results.,14923
+Titanic_nr_records_nr_variables.png,Balancing this dataset by SMOTE would most probably be preferable over undersampling.,14924
+Titanic_scatter-plots.png,Balancing this dataset by SMOTE would be riskier than oversampling by replication.,14925
+Titanic_correlation_heatmap.png,"Applying a non-supervised feature selection based on the redundancy, would not increase the performance of the generality of the training algorithms in this dataset.",14926
+Titanic_boxplots.png,"A scaling transformation is mandatory, in order to improve the Naive Bayes performance in this dataset.",14927
+Titanic_boxplots.png,"A scaling transformation is mandatory, in order to improve the  KNN performance in this dataset.",14928
+Titanic_correlation_heatmap.png,Variables Age and Pclass seem to be useful for classification tasks.,14929
+Titanic_correlation_heatmap.png,Variables SibSp and Pclass seem to be useful for classification tasks.,14930
+Titanic_correlation_heatmap.png,Variables Parch and Pclass seem to be useful for classification tasks.,14931
+Titanic_correlation_heatmap.png,Variables Fare and Pclass seem to be useful for classification tasks.,14932
+Titanic_correlation_heatmap.png,Variables Pclass and Age seem to be useful for classification tasks.,14933
+Titanic_correlation_heatmap.png,Variables SibSp and Age seem to be useful for classification tasks.,14934
+Titanic_correlation_heatmap.png,Variables Parch and Age seem to be useful for classification tasks.,14935
+Titanic_correlation_heatmap.png,Variables Fare and Age seem to be useful for classification tasks.,14936
+Titanic_correlation_heatmap.png,Variables Pclass and SibSp seem to be useful for classification tasks.,14937
+Titanic_correlation_heatmap.png,Variables Age and SibSp seem to be useful for classification tasks.,14938
+Titanic_correlation_heatmap.png,Variables Parch and SibSp seem to be useful for classification tasks.,14939
+Titanic_correlation_heatmap.png,Variables Fare and SibSp seem to be useful for classification tasks.,14940
+Titanic_correlation_heatmap.png,Variables Pclass and Parch seem to be useful for classification tasks.,14941
+Titanic_correlation_heatmap.png,Variables Age and Parch seem to be useful for classification tasks.,14942
+Titanic_correlation_heatmap.png,Variables SibSp and Parch seem to be useful for classification tasks.,14943
+Titanic_correlation_heatmap.png,Variables Fare and Parch seem to be useful for classification tasks.,14944
+Titanic_correlation_heatmap.png,Variables Pclass and Fare seem to be useful for classification tasks.,14945
+Titanic_correlation_heatmap.png,Variables Age and Fare seem to be useful for classification tasks.,14946
+Titanic_correlation_heatmap.png,Variables SibSp and Fare seem to be useful for classification tasks.,14947
+Titanic_correlation_heatmap.png,Variables Parch and Fare seem to be useful for classification tasks.,14948
+Titanic_correlation_heatmap.png,Variable Pclass seems to be relevant for the majority of mining tasks.,14949
+Titanic_correlation_heatmap.png,Variable Age seems to be relevant for the majority of mining tasks.,14950
+Titanic_correlation_heatmap.png,Variable SibSp seems to be relevant for the majority of mining tasks.,14951
+Titanic_correlation_heatmap.png,Variable Parch seems to be relevant for the majority of mining tasks.,14952
+Titanic_correlation_heatmap.png,Variable Fare seems to be relevant for the majority of mining tasks.,14953
+Titanic_decision_tree.png,Variable Pclass is one of the most relevant variables.,14954
+Titanic_decision_tree.png,Variable Age is one of the most relevant variables.,14955
+Titanic_decision_tree.png,Variable SibSp is one of the most relevant variables.,14956
+Titanic_decision_tree.png,Variable Parch is one of the most relevant variables.,14957
+Titanic_decision_tree.png,Variable Fare is one of the most relevant variables.,14958
+Titanic_decision_tree.png,It is possible to state that Pclass is the first most discriminative variable regarding the class.,14959
+Titanic_decision_tree.png,It is possible to state that Age is the first most discriminative variable regarding the class.,14960
+Titanic_decision_tree.png,It is possible to state that SibSp is the first most discriminative variable regarding the class.,14961
+Titanic_decision_tree.png,It is possible to state that Parch is the first most discriminative variable regarding the class.,14962
+Titanic_decision_tree.png,It is possible to state that Fare is the first most discriminative variable regarding the class.,14963
+Titanic_decision_tree.png,It is possible to state that Pclass is the second most discriminative variable regarding the class.,14964
+Titanic_decision_tree.png,It is possible to state that Age is the second most discriminative variable regarding the class.,14965
+Titanic_decision_tree.png,It is possible to state that SibSp is the second most discriminative variable regarding the class.,14966
+Titanic_decision_tree.png,It is possible to state that Parch is the second most discriminative variable regarding the class.,14967
+Titanic_decision_tree.png,It is possible to state that Fare is the second most discriminative variable regarding the class.,14968
+Titanic_decision_tree.png,"The variable Pclass discriminates between the target values, as shown in the decision tree.",14969
+Titanic_decision_tree.png,"The variable Age discriminates between the target values, as shown in the decision tree.",14970
+Titanic_decision_tree.png,"The variable SibSp discriminates between the target values, as shown in the decision tree.",14971
+Titanic_decision_tree.png,"The variable Parch discriminates between the target values, as shown in the decision tree.",14972
+Titanic_decision_tree.png,"The variable Fare discriminates between the target values, as shown in the decision tree.",14973
+Titanic_decision_tree.png,The variable Pclass seems to be one of the two most relevant features.,14974
+Titanic_decision_tree.png,The variable Age seems to be one of the two most relevant features.,14975
+Titanic_decision_tree.png,The variable SibSp seems to be one of the two most relevant features.,14976
+Titanic_decision_tree.png,The variable Parch seems to be one of the two most relevant features.,14977
+Titanic_decision_tree.png,The variable Fare seems to be one of the two most relevant features.,14978
+Titanic_decision_tree.png,The variable Pclass seems to be one of the three most relevant features.,14979
+Titanic_decision_tree.png,The variable Age seems to be one of the three most relevant features.,14980
+Titanic_decision_tree.png,The variable SibSp seems to be one of the three most relevant features.,14981
+Titanic_decision_tree.png,The variable Parch seems to be one of the three most relevant features.,14982
+Titanic_decision_tree.png,The variable Fare seems to be one of the three most relevant features.,14983
+Titanic_decision_tree.png,The variable Pclass seems to be one of the four most relevant features.,14984
+Titanic_decision_tree.png,The variable Age seems to be one of the four most relevant features.,14985
+Titanic_decision_tree.png,The variable SibSp seems to be one of the four most relevant features.,14986
+Titanic_decision_tree.png,The variable Parch seems to be one of the four most relevant features.,14987
+Titanic_decision_tree.png,The variable Fare seems to be one of the four most relevant features.,14988
+Titanic_decision_tree.png,The variable Pclass seems to be one of the five most relevant features.,14989
+Titanic_decision_tree.png,The variable Age seems to be one of the five most relevant features.,14990
+Titanic_decision_tree.png,The variable SibSp seems to be one of the five most relevant features.,14991
+Titanic_decision_tree.png,The variable Parch seems to be one of the five most relevant features.,14992
+Titanic_decision_tree.png,The variable Fare seems to be one of the five most relevant features.,14993
+Titanic_decision_tree.png,It is clear that variable Pclass is one of the two most relevant features.,14994
+Titanic_decision_tree.png,It is clear that variable Age is one of the two most relevant features.,14995
+Titanic_decision_tree.png,It is clear that variable SibSp is one of the two most relevant features.,14996
+Titanic_decision_tree.png,It is clear that variable Parch is one of the two most relevant features.,14997
+Titanic_decision_tree.png,It is clear that variable Fare is one of the two most relevant features.,14998
+Titanic_decision_tree.png,It is clear that variable Pclass is one of the three most relevant features.,14999
+Titanic_decision_tree.png,It is clear that variable Age is one of the three most relevant features.,15000
+Titanic_decision_tree.png,It is clear that variable SibSp is one of the three most relevant features.,15001
+Titanic_decision_tree.png,It is clear that variable Parch is one of the three most relevant features.,15002
+Titanic_decision_tree.png,It is clear that variable Fare is one of the three most relevant features.,15003
+Titanic_decision_tree.png,It is clear that variable Pclass is one of the four most relevant features.,15004
+Titanic_decision_tree.png,It is clear that variable Age is one of the four most relevant features.,15005
+Titanic_decision_tree.png,It is clear that variable SibSp is one of the four most relevant features.,15006
+Titanic_decision_tree.png,It is clear that variable Parch is one of the four most relevant features.,15007
+Titanic_decision_tree.png,It is clear that variable Fare is one of the four most relevant features.,15008
+Titanic_decision_tree.png,It is clear that variable Pclass is one of the five most relevant features.,15009
+Titanic_decision_tree.png,It is clear that variable Age is one of the five most relevant features.,15010
+Titanic_decision_tree.png,It is clear that variable SibSp is one of the five most relevant features.,15011
+Titanic_decision_tree.png,It is clear that variable Parch is one of the five most relevant features.,15012
+Titanic_decision_tree.png,It is clear that variable Fare is one of the five most relevant features.,15013
+Titanic_correlation_heatmap.png,"From the correlation analysis alone, it is clear that there are relevant variables.",15014
+Titanic_correlation_heatmap.png,Variables Age and Pclass are redundant.,15015
+Titanic_correlation_heatmap.png,Variables SibSp and Pclass are redundant.,15016
+Titanic_correlation_heatmap.png,Variables Parch and Pclass are redundant.,15017
+Titanic_correlation_heatmap.png,Variables Fare and Pclass are redundant.,15018
+Titanic_correlation_heatmap.png,Variables Pclass and Age are redundant.,15019
+Titanic_correlation_heatmap.png,Variables SibSp and Age are redundant.,15020
+Titanic_correlation_heatmap.png,Variables Parch and Age are redundant.,15021
+Titanic_correlation_heatmap.png,Variables Fare and Age are redundant.,15022
+Titanic_correlation_heatmap.png,Variables Pclass and SibSp are redundant.,15023
+Titanic_correlation_heatmap.png,Variables Age and SibSp are redundant.,15024
+Titanic_correlation_heatmap.png,Variables Parch and SibSp are redundant.,15025
+Titanic_correlation_heatmap.png,Variables Fare and SibSp are redundant.,15026
+Titanic_correlation_heatmap.png,Variables Pclass and Parch are redundant.,15027
+Titanic_correlation_heatmap.png,Variables Age and Parch are redundant.,15028
+Titanic_correlation_heatmap.png,Variables SibSp and Parch are redundant.,15029
+Titanic_correlation_heatmap.png,Variables Fare and Parch are redundant.,15030
+Titanic_correlation_heatmap.png,Variables Pclass and Fare are redundant.,15031
+Titanic_correlation_heatmap.png,Variables Age and Fare are redundant.,15032
+Titanic_correlation_heatmap.png,Variables SibSp and Fare are redundant.,15033
+Titanic_correlation_heatmap.png,Variables Parch and Fare are redundant.,15034
+Titanic_correlation_heatmap.png,"Variables Fare and Embarked are redundant, but we can’t say the same for the pair Sex and SibSp.",15035
+Titanic_correlation_heatmap.png,"Variables SibSp and Parch are redundant, but we can’t say the same for the pair Sex and Fare.",15036
+Titanic_correlation_heatmap.png,"Variables Parch and Fare are redundant, but we can’t say the same for the pair Sex and Embarked.",15037
+Titanic_correlation_heatmap.png,"Variables SibSp and Embarked are redundant, but we can’t say the same for the pair Pclass and Fare.",15038
+Titanic_correlation_heatmap.png,"Variables SibSp and Parch are redundant, but we can’t say the same for the pair Fare and Embarked.",15039
+Titanic_correlation_heatmap.png,"Variables Pclass and Embarked are redundant, but we can’t say the same for the pair Sex and Age.",15040
+Titanic_correlation_heatmap.png,"Variables Fare and Embarked are redundant, but we can’t say the same for the pair Sex and Parch.",15041
+Titanic_correlation_heatmap.png,"Variables Pclass and SibSp are redundant, but we can’t say the same for the pair Sex and Parch.",15042
+Titanic_correlation_heatmap.png,"Variables SibSp and Parch are redundant, but we can’t say the same for the pair Age and Embarked.",15043
+Titanic_correlation_heatmap.png,"Variables Sex and Age are redundant, but we can’t say the same for the pair Fare and Embarked.",15044
+Titanic_correlation_heatmap.png,"Variables Fare and Embarked are redundant, but we can’t say the same for the pair Age and SibSp.",15045
+Titanic_correlation_heatmap.png,"Variables Fare and Embarked are redundant, but we can’t say the same for the pair Pclass and Age.",15046
+Titanic_correlation_heatmap.png,"Variables Age and Embarked are redundant, but we can’t say the same for the pair SibSp and Fare.",15047
+Titanic_correlation_heatmap.png,"Variables Pclass and Embarked are redundant, but we can’t say the same for the pair Sex and SibSp.",15048
+Titanic_correlation_heatmap.png,"Variables Sex and Age are redundant, but we can’t say the same for the pair SibSp and Parch.",15049
+Titanic_correlation_heatmap.png,"Variables Pclass and Sex are redundant, but we can’t say the same for the pair Age and Fare.",15050
+Titanic_correlation_heatmap.png,"Variables Sex and SibSp are redundant, but we can’t say the same for the pair Age and Embarked.",15051
+Titanic_correlation_heatmap.png,"Variables Sex and Parch are redundant, but we can’t say the same for the pair Age and SibSp.",15052
+Titanic_correlation_heatmap.png,"Variables Sex and Fare are redundant, but we can’t say the same for the pair Pclass and Embarked.",15053
+Titanic_correlation_heatmap.png,"Variables Pclass and SibSp are redundant, but we can’t say the same for the pair Age and Fare.",15054
+Titanic_correlation_heatmap.png,"Variables Pclass and Parch are redundant, but we can’t say the same for the pair Sex and SibSp.",15055
+Titanic_correlation_heatmap.png,"Variables Pclass and Embarked are redundant, but we can’t say the same for the pair SibSp and Parch.",15056
+Titanic_correlation_heatmap.png,"Variables Pclass and Embarked are redundant, but we can’t say the same for the pair Parch and Fare.",15057
+Titanic_correlation_heatmap.png,"Variables Age and SibSp are redundant, but we can’t say the same for the pair Sex and Parch.",15058
+Titanic_correlation_heatmap.png,"Variables Pclass and Sex are redundant, but we can’t say the same for the pair Age and Embarked.",15059
+Titanic_correlation_heatmap.png,"Variables SibSp and Fare are redundant, but we can’t say the same for the pair Parch and Embarked.",15060
+Titanic_correlation_heatmap.png,"Variables Pclass and Sex are redundant, but we can’t say the same for the pair SibSp and Fare.",15061
+Titanic_correlation_heatmap.png,"Variables SibSp and Embarked are redundant, but we can’t say the same for the pair Parch and Fare.",15062
+Titanic_correlation_heatmap.png,"Variables SibSp and Fare are redundant, but we can’t say the same for the pair Age and Embarked.",15063
+Titanic_correlation_heatmap.png,"Variables Pclass and SibSp are redundant, but we can’t say the same for the pair Sex and Embarked.",15064
+Titanic_correlation_heatmap.png,"Variables Pclass and Age are redundant, but we can’t say the same for the pair Sex and SibSp.",15065
+Titanic_correlation_heatmap.png,"Variables Parch and Embarked are redundant, but we can’t say the same for the pair Sex and SibSp.",15066
+Titanic_correlation_heatmap.png,"Variables Age and Embarked are redundant, but we can’t say the same for the pair Pclass and Fare.",15067
+Titanic_correlation_heatmap.png,"Variables Pclass and Embarked are redundant, but we can’t say the same for the pair Age and SibSp.",15068
+Titanic_correlation_heatmap.png,"Variables Parch and Fare are redundant, but we can’t say the same for the pair Sex and SibSp.",15069
+Titanic_correlation_heatmap.png,"Variables Pclass and Age are redundant, but we can’t say the same for the pair SibSp and Fare.",15070
+Titanic_correlation_heatmap.png,"Variables Pclass and Parch are redundant, but we can’t say the same for the pair SibSp and Embarked.",15071
+Titanic_correlation_heatmap.png,"Variables Pclass and SibSp are redundant, but we can’t say the same for the pair Parch and Embarked.",15072
+Titanic_correlation_heatmap.png,"Variables Age and SibSp are redundant, but we can’t say the same for the pair Parch and Embarked.",15073
+Titanic_correlation_heatmap.png,"Variables Pclass and Embarked are redundant, but we can’t say the same for the pair Age and Parch.",15074
+Titanic_correlation_heatmap.png,"Variables SibSp and Embarked are redundant, but we can’t say the same for the pair Sex and Fare.",15075
+Titanic_correlation_heatmap.png,"Variables Age and Fare are redundant, but we can’t say the same for the pair Pclass and SibSp.",15076
+Titanic_correlation_heatmap.png,"Variables Sex and Embarked are redundant, but we can’t say the same for the pair Pclass and Age.",15077
+Titanic_correlation_heatmap.png,"Variables Parch and Embarked are redundant, but we can’t say the same for the pair Sex and Age.",15078
+Titanic_correlation_heatmap.png,"Variables SibSp and Embarked are redundant, but we can’t say the same for the pair Sex and Age.",15079
+Titanic_correlation_heatmap.png,"Variables Pclass and Parch are redundant, but we can’t say the same for the pair Sex and Fare.",15080
+Titanic_correlation_heatmap.png,"Variables Sex and Age are redundant, but we can’t say the same for the pair SibSp and Embarked.",15081
+Titanic_correlation_heatmap.png,"Variables Sex and Embarked are redundant, but we can’t say the same for the pair Pclass and Fare.",15082
+Titanic_correlation_heatmap.png,"Variables Age and Embarked are redundant, but we can’t say the same for the pair Sex and SibSp.",15083
+Titanic_correlation_heatmap.png,"Variables Sex and Parch are redundant, but we can’t say the same for the pair Age and Fare.",15084
+Titanic_correlation_heatmap.png,"Variables SibSp and Fare are redundant, but we can’t say the same for the pair Pclass and Age.",15085
+Titanic_correlation_heatmap.png,"Variables Pclass and Parch are redundant, but we can’t say the same for the pair Fare and Embarked.",15086
+Titanic_correlation_heatmap.png,"Variables Pclass and Age are redundant, but we can’t say the same for the pair Sex and Parch.",15087
+Titanic_correlation_heatmap.png,"Variables Age and Fare are redundant, but we can’t say the same for the pair SibSp and Embarked.",15088
+Titanic_correlation_heatmap.png,"Variables SibSp and Embarked are redundant, but we can’t say the same for the pair Age and Fare.",15089
+Titanic_correlation_heatmap.png,"Variables SibSp and Parch are redundant, but we can’t say the same for the pair Pclass and Embarked.",15090
+Titanic_correlation_heatmap.png,"Variables Fare and Embarked are redundant, but we can’t say the same for the pair Age and Parch.",15091
+Titanic_correlation_heatmap.png,"Variables SibSp and Parch are redundant, but we can’t say the same for the pair Pclass and Fare.",15092
+Titanic_correlation_heatmap.png,"Variables Age and Embarked are redundant, but we can’t say the same for the pair Pclass and SibSp.",15093
+Titanic_correlation_heatmap.png,"Variables Parch and Embarked are redundant, but we can’t say the same for the pair Pclass and Fare.",15094
+Titanic_correlation_heatmap.png,"Variables SibSp and Parch are redundant, but we can’t say the same for the pair Pclass and Sex.",15095
+Titanic_correlation_heatmap.png,"Variables Pclass and Embarked are redundant, but we can’t say the same for the pair Sex and Fare.",15096
+Titanic_correlation_heatmap.png,"Variables Pclass and Sex are redundant, but we can’t say the same for the pair Age and SibSp.",15097
+Titanic_correlation_heatmap.png,"Variables Fare and Embarked are redundant, but we can’t say the same for the pair Pclass and SibSp.",15098
+Titanic_correlation_heatmap.png,"Variables Sex and Parch are redundant, but we can’t say the same for the pair Age and Embarked.",15099
+Titanic_correlation_heatmap.png,"Variables Age and Parch are redundant, but we can’t say the same for the pair Sex and Fare.",15100
+Titanic_correlation_heatmap.png,"Variables Parch and Fare are redundant, but we can’t say the same for the pair Pclass and Age.",15101
+Titanic_correlation_heatmap.png,"Variables Sex and SibSp are redundant, but we can’t say the same for the pair Pclass and Age.",15102
+Titanic_correlation_heatmap.png,"Variables Pclass and Fare are redundant, but we can’t say the same for the pair Age and SibSp.",15103
+Titanic_correlation_heatmap.png,"Variables Sex and Embarked are redundant, but we can’t say the same for the pair SibSp and Fare.",15104
+Titanic_correlation_heatmap.png,"Variables Fare and Embarked are redundant, but we can’t say the same for the pair Sex and Age.",15105
+Titanic_correlation_heatmap.png,"Variables SibSp and Fare are redundant, but we can’t say the same for the pair Pclass and Embarked.",15106
+Titanic_correlation_heatmap.png,"Variables SibSp and Fare are redundant, but we can’t say the same for the pair Sex and Age.",15107
+Titanic_correlation_heatmap.png,"Variables SibSp and Parch are redundant, but we can’t say the same for the pair Pclass and Age.",15108
+Titanic_correlation_heatmap.png,"Variables Pclass and Sex are redundant, but we can’t say the same for the pair Age and Parch.",15109
+Titanic_correlation_heatmap.png,"Variables Pclass and Sex are redundant, but we can’t say the same for the pair Fare and Embarked.",15110
+Titanic_correlation_heatmap.png,"Variables Pclass and Age are redundant, but we can’t say the same for the pair Fare and Embarked.",15111
+Titanic_correlation_heatmap.png,"Variables Pclass and Sex are redundant, but we can’t say the same for the pair Parch and Fare.",15112
+Titanic_correlation_heatmap.png,"Variables Pclass and SibSp are redundant, but we can’t say the same for the pair Sex and Fare.",15113
+Titanic_correlation_heatmap.png,"Variables Sex and Age are redundant, but we can’t say the same for the pair Pclass and Fare.",15114
+Titanic_correlation_heatmap.png,"Variables Pclass and Fare are redundant, but we can’t say the same for the pair Age and Embarked.",15115
+Titanic_correlation_heatmap.png,"Variables Age and Embarked are redundant, but we can’t say the same for the pair Sex and Parch.",15116
+Titanic_correlation_heatmap.png,"Variables Age and Parch are redundant, but we can’t say the same for the pair Fare and Embarked.",15117
+Titanic_correlation_heatmap.png,"Variables Sex and Fare are redundant, but we can’t say the same for the pair SibSp and Parch.",15118
+Titanic_correlation_heatmap.png,The variable Pclass can be discarded without risking losing information.,15119
+Titanic_correlation_heatmap.png,The variable Age can be discarded without risking losing information.,15120
+Titanic_correlation_heatmap.png,The variable SibSp can be discarded without risking losing information.,15121
+Titanic_correlation_heatmap.png,The variable Parch can be discarded without risking losing information.,15122
+Titanic_correlation_heatmap.png,The variable Fare can be discarded without risking losing information.,15123
+Titanic_correlation_heatmap.png,One of the variables Age or Pclass can be discarded without losing information.,15124
+Titanic_correlation_heatmap.png,One of the variables SibSp or Pclass can be discarded without losing information.,15125
+Titanic_correlation_heatmap.png,One of the variables Parch or Pclass can be discarded without losing information.,15126
+Titanic_correlation_heatmap.png,One of the variables Fare or Pclass can be discarded without losing information.,15127
+Titanic_correlation_heatmap.png,One of the variables Pclass or Age can be discarded without losing information.,15128
+Titanic_correlation_heatmap.png,One of the variables SibSp or Age can be discarded without losing information.,15129
+Titanic_correlation_heatmap.png,One of the variables Parch or Age can be discarded without losing information.,15130
+Titanic_correlation_heatmap.png,One of the variables Fare or Age can be discarded without losing information.,15131
+Titanic_correlation_heatmap.png,One of the variables Pclass or SibSp can be discarded without losing information.,15132
+Titanic_correlation_heatmap.png,One of the variables Age or SibSp can be discarded without losing information.,15133
+Titanic_correlation_heatmap.png,One of the variables Parch or SibSp can be discarded without losing information.,15134
+Titanic_correlation_heatmap.png,One of the variables Fare or SibSp can be discarded without losing information.,15135
+Titanic_correlation_heatmap.png,One of the variables Pclass or Parch can be discarded without losing information.,15136
+Titanic_correlation_heatmap.png,One of the variables Age or Parch can be discarded without losing information.,15137
+Titanic_correlation_heatmap.png,One of the variables SibSp or Parch can be discarded without losing information.,15138
+Titanic_correlation_heatmap.png,One of the variables Fare or Parch can be discarded without losing information.,15139
+Titanic_correlation_heatmap.png,One of the variables Pclass or Fare can be discarded without losing information.,15140
+Titanic_correlation_heatmap.png,One of the variables Age or Fare can be discarded without losing information.,15141
+Titanic_correlation_heatmap.png,One of the variables SibSp or Fare can be discarded without losing information.,15142
+Titanic_correlation_heatmap.png,One of the variables Parch or Fare can be discarded without losing information.,15143
+Titanic_histograms_numeric.png,The existence of outliers is one of the problems to tackle in this dataset.,15144
+Titanic_boxplots.png,The boxplots presented show a large number of outliers for most of the numeric variables.,15145
+Titanic_boxplots.png,The histograms presented show a large number of outliers for most of the numeric variables.,15146
+Titanic_histograms_numeric.png,At least 50 of the variables present outliers.,15147
+Titanic_boxplots.png,At least 60 of the variables present outliers.,15148
+Titanic_histograms_numeric.png,At least 75 of the variables present outliers.,15149
+Titanic_histograms_numeric.png,At least 85 of the variables present outliers.,15150
+Titanic_boxplots.png,Variable Pclass presents some outliers.,15151
+Titanic_histograms_numeric.png,Variable Age presents some outliers.,15152
+Titanic_boxplots.png,Variable SibSp presents some outliers.,15153
+Titanic_boxplots.png,Variable Parch presents some outliers.,15154
+Titanic_histograms_numeric.png,Variable Fare presents some outliers.,15155
+Titanic_boxplots.png,Variable Pclass doesn’t have any outliers.,15156
+Titanic_histograms_numeric.png,Variable Age doesn’t have any outliers.,15157
+Titanic_histograms_numeric.png,Variable SibSp doesn’t have any outliers.,15158
+Titanic_boxplots.png,Variable Parch doesn’t have any outliers.,15159
+Titanic_boxplots.png,Variable Fare doesn’t have any outliers.,15160
+Titanic_histograms_numeric.png,Variable Pclass shows some outlier values.,15161
+Titanic_boxplots.png,Variable Age shows some outlier values.,15162
+Titanic_histograms_numeric.png,Variable SibSp shows some outlier values.,15163
+Titanic_boxplots.png,Variable Parch shows some outlier values.,15164
+Titanic_histograms_numeric.png,Variable Fare shows some outlier values.,15165
+Titanic_boxplots.png,Variable Pclass shows a high number of outlier values.,15166
+Titanic_histograms_numeric.png,Variable Age shows a high number of outlier values.,15167
+Titanic_boxplots.png,Variable SibSp shows a high number of outlier values.,15168
+Titanic_histograms_numeric.png,Variable Parch shows a high number of outlier values.,15169
+Titanic_boxplots.png,Variable Fare shows a high number of outlier values.,15170
+Titanic_histograms_numeric.png,Outliers seem to be a problem in the dataset.,15171
+Titanic_histograms_numeric.png,"It is clear that variable Age shows some outliers, but we can’t be sure of the same for variable Pclass.",15172
+Titanic_boxplots.png,"It is clear that variable SibSp shows some outliers, but we can’t be sure of the same for variable Pclass.",15173
+Titanic_histograms_numeric.png,"It is clear that variable Parch shows some outliers, but we can’t be sure of the same for variable Pclass.",15174
+Titanic_boxplots.png,"It is clear that variable Fare shows some outliers, but we can’t be sure of the same for variable Pclass.",15175
+Titanic_boxplots.png,"It is clear that variable Pclass shows some outliers, but we can’t be sure of the same for variable Age.",15176
+Titanic_boxplots.png,"It is clear that variable SibSp shows some outliers, but we can’t be sure of the same for variable Age.",15177
+Titanic_histograms_numeric.png,"It is clear that variable Parch shows some outliers, but we can’t be sure of the same for variable Age.",15178
+Titanic_histograms_numeric.png,"It is clear that variable Fare shows some outliers, but we can’t be sure of the same for variable Age.",15179
+Titanic_boxplots.png,"It is clear that variable Pclass shows some outliers, but we can’t be sure of the same for variable SibSp.",15180
+Titanic_boxplots.png,"It is clear that variable Age shows some outliers, but we can’t be sure of the same for variable SibSp.",15181
+Titanic_histograms_numeric.png,"It is clear that variable Parch shows some outliers, but we can’t be sure of the same for variable SibSp.",15182
+Titanic_boxplots.png,"It is clear that variable Fare shows some outliers, but we can’t be sure of the same for variable SibSp.",15183
+Titanic_histograms_numeric.png,"It is clear that variable Pclass shows some outliers, but we can’t be sure of the same for variable Parch.",15184
+Titanic_histograms_numeric.png,"It is clear that variable Age shows some outliers, but we can’t be sure of the same for variable Parch.",15185
+Titanic_boxplots.png,"It is clear that variable SibSp shows some outliers, but we can’t be sure of the same for variable Parch.",15186
+Titanic_boxplots.png,"It is clear that variable Fare shows some outliers, but we can’t be sure of the same for variable Parch.",15187
+Titanic_histograms_numeric.png,"It is clear that variable Pclass shows some outliers, but we can’t be sure of the same for variable Fare.",15188
+Titanic_histograms_numeric.png,"It is clear that variable Age shows some outliers, but we can’t be sure of the same for variable Fare.",15189
+Titanic_histograms_numeric.png,"It is clear that variable SibSp shows some outliers, but we can’t be sure of the same for variable Fare.",15190
+Titanic_histograms_numeric.png,"It is clear that variable Parch shows some outliers, but we can’t be sure of the same for variable Fare.",15191
+Titanic_boxplots.png,Those boxplots show that the data is not normalized.,15192
+Titanic_boxplots.png,Variable Pclass is balanced.,15193
+Titanic_histograms_numeric.png,Variable Age is balanced.,15194
+Titanic_boxplots.png,Variable SibSp is balanced.,15195
+Titanic_histograms_numeric.png,Variable Parch is balanced.,15196
+Titanic_histograms_numeric.png,Variable Fare is balanced.,15197
+Titanic_histograms.png,The variable Pclass can be seen as ordinal without losing information.,15198
+Titanic_histograms.png,The variable Sex can be seen as ordinal without losing information.,15199
+Titanic_histograms.png,The variable Age can be seen as ordinal without losing information.,15200
+Titanic_histograms.png,The variable SibSp can be seen as ordinal without losing information.,15201
+Titanic_histograms.png,The variable Parch can be seen as ordinal without losing information.,15202
+Titanic_histograms.png,The variable Fare can be seen as ordinal without losing information.,15203
+Titanic_histograms.png,The variable Embarked can be seen as ordinal without losing information.,15204
+Titanic_histograms.png,The variable Pclass can be seen as ordinal.,15205
+Titanic_histograms.png,The variable Sex can be seen as ordinal.,15206
+Titanic_histograms.png,The variable Age can be seen as ordinal.,15207
+Titanic_histograms.png,The variable SibSp can be seen as ordinal.,15208
+Titanic_histograms.png,The variable Parch can be seen as ordinal.,15209
+Titanic_histograms.png,The variable Fare can be seen as ordinal.,15210
+Titanic_histograms.png,The variable Embarked can be seen as ordinal.,15211
+Titanic_histograms.png,"All variables, but the class, should be dealt with as numeric.",15212
+Titanic_histograms.png,"All variables, but the class, should be dealt with as binary.",15213
+Titanic_histograms.png,"All variables, but the class, should be dealt with as date.",15214
+Titanic_histograms.png,"All variables, but the class, should be dealt with as symbolic.",15215
+Titanic_correlation_heatmap.png,The intrinsic dimensionality of this dataset is 50.,15216
+Titanic_correlation_heatmap.png,The intrinsic dimensionality of this dataset is 93.,15217
+Titanic_correlation_heatmap.png,The intrinsic dimensionality of this dataset is 47.,15218
+Titanic_correlation_heatmap.png,The intrinsic dimensionality of this dataset is 12.,15219
+Titanic_correlation_heatmap.png,The intrinsic dimensionality of this dataset is 38.,15220
+Titanic_nr_records_nr_variables.png,We face the curse of dimensionality when training a classifier with this dataset.,15221
+Titanic_nr_records_nr_variables.png,"Given the number of records and that some variables are numeric, we might be facing the curse of dimensionality.",15222
+Titanic_nr_records_nr_variables.png,"Given the number of records and that some variables are binary, we might be facing the curse of dimensionality.",15223
+Titanic_nr_records_nr_variables.png,"Given the number of records and that some variables are date, we might be facing the curse of dimensionality.",15224
+Titanic_nr_records_nr_variables.png,"Given the number of records and that some variables are symbolic, we might be facing the curse of dimensionality.",15225