The model takes in 23 variables as an input and then produces a 1 if the model thinks they will default and a 0 if not.


The variables can be describers here: 

X1: Amount of the given credit (NT dollar): it includes both the individual consumer credit and his/her family (supplementary) credit.
X2: Gender (1 = male; 2 = female).
X3: Education (1 = graduate school; 2 = university; 3 = high school; 4 = others).
X4: Marital status (1 = married; 2 = single; 3 = others).
X5: Age (year).
X6 - X11: History of past payment. We tracked the past monthly payment records from the past 6 months as follows: X6 = the most recent repayment status; ;X11 = the repayment status from 6 months ago. The measurement scale for the repayment status is: -1 = pay duly; 1 = payment delay for one month; 2 = payment delay for two months; . . .; 8 = payment delay for eight months; 9 = payment delay for nine months and above.
X12-X17: Amount of bill statement (NT dollar for the past 6 months). X12 = amount of bill statement from the most recent bill;  X17 = amount of bill statement from 6 months ago.
X18-X23: Amount of previous payment (NT dollar for the past 6 months). X18 = amount paid in the most recent month; X23 = amount paid in 6 months ago.


Example data set Input:

                                                                                                                                      
LIMIT_BALSEXEDUCATIONMARRIAGEAGEPAY_0PAY_2PAY_3PAY_4PAY_5PAY_6BILL_AMT1BILL_AMT2BILL_AMT3BILL_AMT4BILL_AMT5BILL_AMT6PAY_AMT1PAY_AMT2PAY_AMT3PAY_AMT4PAY_AMT5PAY_AMT6
200002212422-1-1-2-23913310268900006890000
12000022226-120002268217252682327234553261010001000100002000