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Hotel_Reservations_overfitting_rf.png;A multi-line chart showing the overfitting of random forest where the y-axis represents the accuracy and the x-axis represents the number of estimators ranging from 2 to 2002. |
Hotel_Reservations_overfitting_knn.png;A multi-line chart showing the overfitting of k-nearest neighbors where the y-axis represents the accuracy and the x-axis represents the number of neighbors ranging from 1 to 23. |
Hotel_Reservations_overfitting_decision_tree.png;A multi-line chart showing the overfitting of a decision tree where the y-axis represents the accuracy and the x-axis represents the max depth ranging from 2 to 25. |
Hotel_Reservations_overfitting_dt_acc_rec.png;A multi-line chart showing the overfitting of decision tree where the y-axis represents the performance of both accuracy and recall and the x-axis represents the max depth ranging from 2 to 25. |
Hotel_Reservations_pca.png;A bar chart showing the explained variance ratio of [] principal components. |
Hotel_Reservations_correlation_heatmap.png;A heatmap showing the correlation between the variables of the dataset. The variables are []. |
Hotel_Reservations_boxplots.png;A set of boxplots of the variables []. |
Hotel_Reservations_histograms_symbolic.png;A set of bar charts of the variables []. |
Hotel_Reservations_class_histogram.png;A bar chart showing the distribution of the target variable []. |
Hotel_Reservations_nr_records_nr_variables.png;A bar chart showing the number of records and variables of the dataset. |
Hotel_Reservations_histograms_numeric.png;A set of histograms of the variables []. |
StressLevelDataset_decision_tree.png;An image showing a decision tree with depth = 2 where the first decision is made with the condition [] and the second with the condition []. |
StressLevelDataset_overfitting_mlp.png;A multi-line chart showing the overfitting of a mlp where the y-axis represents the accuracy and the x-axis represents the number of iterations ranging from 100 to 1000. |
StressLevelDataset_overfitting_gb.png;A multi-line chart showing the overfitting of gradient boosting where the y-axis represents the accuracy and the x-axis represents the number of estimators ranging from 2 to 2002. |
StressLevelDataset_overfitting_rf.png;A multi-line chart showing the overfitting of random forest where the y-axis represents the accuracy and the x-axis represents the number of estimators ranging from 2 to 2002. |
StressLevelDataset_overfitting_knn.png;A multi-line chart showing the overfitting of k-nearest neighbors where the y-axis represents the accuracy and the x-axis represents the number of neighbors ranging from 1 to 23. |
StressLevelDataset_overfitting_decision_tree.png;A multi-line chart showing the overfitting of a decision tree where the y-axis represents the accuracy and the x-axis represents the max depth ranging from 2 to 25. |
StressLevelDataset_pca.png;A bar chart showing the explained variance ratio of [] principal components. |
StressLevelDataset_correlation_heatmap.png;A heatmap showing the correlation between the variables of the dataset. The variables are []. |
StressLevelDataset_boxplots.png;A set of boxplots of the variables []. |
StressLevelDataset_histograms_symbolic.png;A set of bar charts of the variables []. |
StressLevelDataset_class_histogram.png;A bar chart showing the distribution of the target variable []. |
StressLevelDataset_nr_records_nr_variables.png;A bar chart showing the number of records and variables of the dataset. |
StressLevelDataset_histograms_numeric.png;A set of histograms of the variables []. |
WineQT_decision_tree.png;An image showing a decision tree with depth = 2 where the first decision is made with the condition [] and the second with the condition []. |
WineQT_overfitting_mlp.png;A multi-line chart showing the overfitting of a mlp where the y-axis represents the accuracy and the x-axis represents the number of iterations ranging from 100 to 1000. |
WineQT_overfitting_gb.png;A multi-line chart showing the overfitting of gradient boosting where the y-axis represents the accuracy and the x-axis represents the number of estimators ranging from 2 to 2002. |
WineQT_overfitting_rf.png;A multi-line chart showing the overfitting of random forest where the y-axis represents the accuracy and the x-axis represents the number of estimators ranging from 2 to 2002. |
WineQT_overfitting_knn.png;A multi-line chart showing the overfitting of k-nearest neighbors where the y-axis represents the accuracy and the x-axis represents the number of neighbors ranging from 1 to 23. |
WineQT_overfitting_decision_tree.png;A multi-line chart showing the overfitting of a decision tree where the y-axis represents the accuracy and the x-axis represents the max depth ranging from 2 to 25. |
WineQT_pca.png;A bar chart showing the explained variance ratio of [] principal components. |
WineQT_correlation_heatmap.png;A heatmap showing the correlation between the variables of the dataset. The variables are []. |
WineQT_boxplots.png;A set of boxplots of the variables []. |
WineQT_class_histogram.png;A bar chart showing the distribution of the target variable []. |
WineQT_nr_records_nr_variables.png;A bar chart showing the number of records and variables of the dataset. |
WineQT_histograms_numeric.png;A set of histograms of the variables []. |
loan_data_decision_tree.png;An image showing a decision tree with depth = 2 where the first decision is made with the condition [] and the second with the condition []. |
loan_data_overfitting_mlp.png;A multi-line chart showing the overfitting of a mlp where the y-axis represents the accuracy and the x-axis represents the number of iterations ranging from 100 to 1000. |
loan_data_overfitting_gb.png;A multi-line chart showing the overfitting of gradient boosting where the y-axis represents the accuracy and the x-axis represents the number of estimators ranging from 2 to 2002. |
loan_data_overfitting_rf.png;A multi-line chart showing the overfitting of random forest where the y-axis represents the accuracy and the x-axis represents the number of estimators ranging from 2 to 2002. |
loan_data_overfitting_knn.png;A multi-line chart showing the overfitting of k-nearest neighbors where the y-axis represents the accuracy and the x-axis represents the number of neighbors ranging from 1 to 23. |
loan_data_overfitting_decision_tree.png;A multi-line chart showing the overfitting of a decision tree where the y-axis represents the accuracy and the x-axis represents the max depth ranging from 2 to 25. |
loan_data_overfitting_dt_acc_rec.png;A multi-line chart showing the overfitting of decision tree where the y-axis represents the performance of both accuracy and recall and the x-axis represents the max depth ranging from 2 to 25. |
loan_data_pca.png;A bar chart showing the explained variance ratio of [] principal components. |
loan_data_correlation_heatmap.png;A heatmap showing the correlation between the variables of the dataset. The variables are []. |
loan_data_boxplots.png;A set of boxplots of the variables []. |
loan_data_histograms_symbolic.png;A set of bar charts of the variables []. |
loan_data_mv.png;A bar chart showing the number of missing values per variable of the dataset. The variables that have missing values are: []. |
loan_data_class_histogram.png;A bar chart showing the distribution of the target variable []. |
loan_data_nr_records_nr_variables.png;A bar chart showing the number of records and variables of the dataset. |
loan_data_histograms_numeric.png;A set of histograms of the variables []. |
Dry_Bean_Dataset_decision_tree.png;An image showing a decision tree with depth = 2 where the first decision is made with the condition [] and the second with the condition []. |
Dry_Bean_Dataset_overfitting_mlp.png;A multi-line chart showing the overfitting of a mlp where the y-axis represents the accuracy and the x-axis represents the number of iterations ranging from 100 to 1000. |
Dry_Bean_Dataset_overfitting_gb.png;A multi-line chart showing the overfitting of gradient boosting where the y-axis represents the accuracy and the x-axis represents the number of estimators ranging from 2 to 2002. |
Dry_Bean_Dataset_overfitting_rf.png;A multi-line chart showing the overfitting of random forest where the y-axis represents the accuracy and the x-axis represents the number of estimators ranging from 2 to 2002. |
Dry_Bean_Dataset_overfitting_knn.png;A multi-line chart showing the overfitting of k-nearest neighbors where the y-axis represents the accuracy and the x-axis represents the number of neighbors ranging from 1 to 23. |
Dry_Bean_Dataset_overfitting_decision_tree.png;A multi-line chart showing the overfitting of a decision tree where the y-axis represents the accuracy and the x-axis represents the max depth ranging from 2 to 25. |
Dry_Bean_Dataset_pca.png;A bar chart showing the explained variance ratio of [] principal components. |
Dry_Bean_Dataset_correlation_heatmap.png;A heatmap showing the correlation between the variables of the dataset. The variables are []. |
Dry_Bean_Dataset_boxplots.png;A set of boxplots of the variables []. |
Dry_Bean_Dataset_class_histogram.png;A bar chart showing the distribution of the target variable []. |
Dry_Bean_Dataset_nr_records_nr_variables.png;A bar chart showing the number of records and variables of the dataset. |
Dry_Bean_Dataset_histograms_numeric.png;A set of histograms of the variables []. |
credit_customers_decision_tree.png;An image showing a decision tree with depth = 2 where the first decision is made with the condition [] and the second with the condition []. |
credit_customers_overfitting_mlp.png;A multi-line chart showing the overfitting of a mlp where the y-axis represents the accuracy and the x-axis represents the number of iterations ranging from 100 to 1000. |
credit_customers_overfitting_gb.png;A multi-line chart showing the overfitting of gradient boosting where the y-axis represents the accuracy and the x-axis represents the number of estimators ranging from 2 to 2002. |
credit_customers_overfitting_rf.png;A multi-line chart showing the overfitting of random forest where the y-axis represents the accuracy and the x-axis represents the number of estimators ranging from 2 to 2002. |
credit_customers_overfitting_knn.png;A multi-line chart showing the overfitting of k-nearest neighbors where the y-axis represents the accuracy and the x-axis represents the number of neighbors ranging from 1 to 23. |
credit_customers_overfitting_decision_tree.png;A multi-line chart showing the overfitting of a decision tree where the y-axis represents the accuracy and the x-axis represents the max depth ranging from 2 to 25. |
credit_customers_overfitting_dt_acc_rec.png;A multi-line chart showing the overfitting of decision tree where the y-axis represents the performance of both accuracy and recall and the x-axis represents the max depth ranging from 2 to 25. |
credit_customers_pca.png;A bar chart showing the explained variance ratio of [] principal components. |
credit_customers_correlation_heatmap.png;A heatmap showing the correlation between the variables of the dataset. The variables are []. |
credit_customers_boxplots.png;A set of boxplots of the variables []. |
credit_customers_histograms_symbolic.png;A set of bar charts of the variables []. |
credit_customers_class_histogram.png;A bar chart showing the distribution of the target variable []. |
credit_customers_nr_records_nr_variables.png;A bar chart showing the number of records and variables of the dataset. |
credit_customers_histograms_numeric.png;A set of histograms of the variables []. |
weatherAUS_decision_tree.png;An image showing a decision tree with depth = 2 where the first decision is made with the condition [] and the second with the condition []. |
weatherAUS_overfitting_mlp.png;A multi-line chart showing the overfitting of a mlp where the y-axis represents the accuracy and the x-axis represents the number of iterations ranging from 100 to 1000. |
weatherAUS_overfitting_gb.png;A multi-line chart showing the overfitting of gradient boosting where the y-axis represents the accuracy and the x-axis represents the number of estimators ranging from 2 to 2002. |
weatherAUS_overfitting_rf.png;A multi-line chart showing the overfitting of random forest where the y-axis represents the accuracy and the x-axis represents the number of estimators ranging from 2 to 2002. |
weatherAUS_overfitting_knn.png;A multi-line chart showing the overfitting of k-nearest neighbors where the y-axis represents the accuracy and the x-axis represents the number of neighbors ranging from 1 to 23. |
weatherAUS_overfitting_decision_tree.png;A multi-line chart showing the overfitting of a decision tree where the y-axis represents the accuracy and the x-axis represents the max depth ranging from 2 to 25. |
weatherAUS_overfitting_dt_acc_rec.png;A multi-line chart showing the overfitting of decision tree where the y-axis represents the performance of both accuracy and recall and the x-axis represents the max depth ranging from 2 to 25. |
weatherAUS_pca.png;A bar chart showing the explained variance ratio of [] principal components. |
weatherAUS_correlation_heatmap.png;A heatmap showing the correlation between the variables of the dataset. The variables are []. |
weatherAUS_boxplots.png;A set of boxplots of the variables []. |
weatherAUS_histograms_symbolic.png;A set of bar charts of the variables []. |
weatherAUS_mv.png;A bar chart showing the number of missing values per variable of the dataset. The variables that have missing values are: []. |
weatherAUS_class_histogram.png;A bar chart showing the distribution of the target variable []. |
weatherAUS_nr_records_nr_variables.png;A bar chart showing the number of records and variables of the dataset. |
weatherAUS_histograms_numeric.png;A set of histograms of the variables []. |
car_insurance_decision_tree.png;An image showing a decision tree with depth = 2 where the first decision is made with the condition [] and the second with the condition []. |
car_insurance_overfitting_mlp.png;A multi-line chart showing the overfitting of a mlp where the y-axis represents the accuracy and the x-axis represents the number of iterations ranging from 100 to 1000. |
car_insurance_overfitting_gb.png;A multi-line chart showing the overfitting of gradient boosting where the y-axis represents the accuracy and the x-axis represents the number of estimators ranging from 2 to 2002. |
car_insurance_overfitting_rf.png;A multi-line chart showing the overfitting of random forest where the y-axis represents the accuracy and the x-axis represents the number of estimators ranging from 2 to 2002. |
car_insurance_overfitting_knn.png;A multi-line chart showing the overfitting of k-nearest neighbors where the y-axis represents the accuracy and the x-axis represents the number of neighbors ranging from 1 to 23. |
car_insurance_overfitting_decision_tree.png;A multi-line chart showing the overfitting of a decision tree where the y-axis represents the accuracy and the x-axis represents the max depth ranging from 2 to 25. |
car_insurance_overfitting_dt_acc_rec.png;A multi-line chart showing the overfitting of decision tree where the y-axis represents the performance of both accuracy and recall and the x-axis represents the max depth ranging from 2 to 25. |
car_insurance_pca.png;A bar chart showing the explained variance ratio of [] principal components. |
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