Datasets:
MinaMila
/
GermanCredit_train_CDF_lr

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status of existing checking account_0 to less than 200 DM
int64
0
1
status of existing checking account_200 DM or more
int64
0
1
status of existing checking account_less than 0 DM
int64
0
1
status of existing checking account_no checking account
int64
0
1
purpose of credit_for business
int64
0
1
purpose of credit_for education
int64
0
1
purpose of credit_for other reasons
int64
0
1
purpose of credit_for repairs
int64
0
1
purpose of credit_for retraining
int64
0
1
purpose of credit_to buy a new car
int64
0
1
purpose of credit_to buy a radio or television
int64
0
1
purpose of credit_to buy a used car
int64
0
1
purpose of credit_to buy domestic appliances
int64
0
1
purpose of credit_to buy furniture or equipment
int64
0
1
sex_male
int64
0
1
housing_owned
int64
0
1
housing_provided for free
int64
0
1
housing_rented
int64
0
1
job status_manager, self-employed, or highly qualified
int64
0
1
job status_skilled worker or official
int64
0
1
job status_unemployed or unskilled (non-resident)
int64
0
1
job status_unskilled worker (resident)
int64
0
1
marital status_divorced / separated
int64
0
1
marital status_divorced / separated / married
int64
0
1
marital status_married / widowed
int64
0
1
marital status_single
int64
0
1
duration in months
int64
4
72
credit amount
int64
250
18.4k
age
int64
20
75
credit worthiness
int64
0
1
0
0
0
1
0
1
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1
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1
12
2,096
49
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1
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1
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1
18
4,439
33
1
1
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0
0
1
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0
1
0
6
484
28
1
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1
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1
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12
3,499
29
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0
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1
1
0
0
1
0
1
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0
0
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1
12
5,801
49
1
0
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1
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0
0
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0
0
0
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1
1
0
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1
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1
0
0
0
1
0
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10
2,146
23
1
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1
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1
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1
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1
6
1,872
36
1
0
0
1
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1
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1
1
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1
6
1,361
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1
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1
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1
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0
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0
0
0
0
0
1
1
0
0
1
0
0
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0
1
0
0
36
8,065
25
0
0
0
1
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0
0
0
0
0
0
0
0
0
1
0
0
0
1
0
1
0
0
0
1
0
0
18
2,124
24
0
0
0
1
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0
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0
0
0
0
0
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1
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0
1
0
0
1
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1
48
7,119
53
0
0
0
0
1
0
0
0
0
0
1
0
0
0
0
0
1
0
0
0
1
0
0
0
0
0
1
9
2,134
48
1
0
0
1
0
0
0
0
0
0
0
1
0
0
0
0
1
0
0
1
0
0
0
0
0
0
1
27
3,416
27
1
0
0
0
1
0
0
0
0
0
1
0
0
0
0
0
1
0
0
0
1
0
0
0
1
0
0
21
5,003
29
0
0
0
1
0
0
0
0
0
0
1
0
0
0
0
1
0
1
0
0
1
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0
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1
24
1,333
43
0
0
0
1
0
0
0
0
0
0
1
0
0
0
0
1
1
0
0
0
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1
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1
21
1,647
40
0
1
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0
0
0
0
0
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0
0
1
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0
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1
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0
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1
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0
0
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1
24
1,216
38
0
0
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1
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0
0
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1
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0
0
0
0
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1
0
1
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12
902
21
0
1
0
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0
1
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1
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1
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1
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72
5,595
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0
0
0
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1
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0
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0
1
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0
1
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1
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1
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6
362
52
1
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1
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1
1
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1
0
0
15
3,568
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1
1
0
0
0
1
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0
0
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1
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1
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1
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30
4,280
26
0
1
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1
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1
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1
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1
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1
60
9,157
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1
0
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1
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1
1
1
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1
15
1,520
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1
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1
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10
2,210
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1
18
2,473
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1
18
1,582
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1
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1
36
8,335
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1,239
61
1
1
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1
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1,444
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1
1
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2,528
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1
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2,223
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1,591
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1
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11
1,577
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1
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1
1
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36
8,947
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1
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42
3,965
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1
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959
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1,549
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1
24
7,814
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1
0
0
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1
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0
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1
0
1
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12
1,555
55
0
0
1
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1
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1
1
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0
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9
1,126
49
1
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1
1
0
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48
3,609
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1
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1
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1
1
1
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10
1,275
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1
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8,613
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1
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2,124
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2,613
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1,042
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2,969
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1,024
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1,163
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1,297
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3,249
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745
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30
2,991
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3,878
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7,882
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15
1,532
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11
1,393
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3,394
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6,758
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42
3,965
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24
1,216
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18
3,590
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1
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15
6,850
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12
1,474
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24
1,193
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1,216
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24
3,092
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18
1,961
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1
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12
2,762
25
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343
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629
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3,972
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24
2,039
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18
2,775
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12
1,200
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1,216
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12
1,158
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30
2,333
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1,249
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48
8,487
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24
2,910
34
1
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1
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0
0
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0
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0
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1
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1
0
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1
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1
24
2,028
30
1
1
0
0
0
0
0
0
0
0
0
1
0
0
0
1
1
0
0
0
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1
24
1,216
38
0
0
0
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1
1
0
0
0
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0
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0
1
0
0
1
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1
36
7,980
27
0
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1
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12
1,963
31
1
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1
0
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3,092
22
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24
1,851
33
1
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15
2,708
27
1
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1,533
38
1
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1,164
51
1
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18
7,511
51
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1,963
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1,333
43
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48
3,914
38
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2,579
33
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36
3,249
39
1
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4,605
24
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1,198
35
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24
1,275
36
1