=== Run information === Evaluator: weka.attributeSelection.InfoGainAttributeEval Search: weka.attributeSelection.Ranker -T -1.7976931348623157E308 -N -1 Relation: Card_Mining.txt Instances: 892 Attributes: 27 Instance_number Acct_ID Client_Age Client_Sex Acct_Frequency Acct_YearOpened Client_District_ID Acct_District_ID District_A3 District_A4 District_A5 District_A6 District_A7 District_A8 District_A9 District_A10 District_A11 District_A12 District_A13 District_A14 District_A15 District_A16 Loan_Status_I Loan_Status_II Trans_Avg_Balance Disp_Add_Users CardType Evaluation mode: evaluate on all training data === Attribute Selection on all input data === Search Method: Attribute ranking. Attribute Evaluator (supervised, Class (nominal): 27 CardType): Information Gain Ranking Filter Ranked attributes: 0.47367 3 Client_Age 0.12299 8 Acct_District_ID 0.11712 7 Client_District_ID 0.09685 25 Trans_Avg_Balance 0.01591 6 Acct_YearOpened 0.00791 9 District_A3 0.00704 23 Loan_Status_I 0.00306 5 Acct_Frequency 0.00301 26 Disp_Add_Users 0.00291 24 Loan_Status_II 0.0019 4 Client_Sex 0 10 District_A4 0 11 District_A5 0 2 Acct_ID 0 1 Instance_number 0 19 District_A13 0 18 District_A12 0 20 District_A14 0 22 District_A16 0 21 District_A15 0 17 District_A11 0 13 District_A7 0 12 District_A6 0 14 District_A8 0 16 District_A10 0 15 District_A9 Selected attributes: 3,8,7,25,6,9,23,5,26,24,4,10,11,2,1,19,18,20,22,21,17,13,12,14,16,15 : 26