I am struggling to understand the meaning of some features of the german credit dataset (https://archive.ics.uci.edu/ml/datasets/statlog+(german+credit+data)).
I am particularly interested in, the categorical feature checking_status (Status of existing checking account) which has 4 possible values :
- '< 0'
- 'no checking'
I am not a banking expert but my intuition would be than the higher the checking status the higher the probability to be classified as good. TO check my intuition I computed the proportion of applicant classified as good in the dataset depending on their checking_status values. The results were surprising :
- no checking : 88 %
- <0 : 35 %
- 0<=X<200 : 42 %
- '>=200' : 12 %
Can be read as : 88 % of applicants with 'no checking' are classified as good.
So according to german credit dataset it is harder to have a credit with more money '>=200' < '<0' and it is much easier when the applicant does not have a bank account !
Any idea / links on the interpretation of this feature ?