?? credit-g.arff
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% Description of the German credit dataset.% % 1. Title: German Credit data% % 2. Source Information% % Professor Dr. Hans Hofmann % Institut f"ur Statistik und "Okonometrie % Universit"at Hamburg % FB Wirtschaftswissenschaften % Von-Melle-Park 5 % 2000 Hamburg 13 % % 3. Number of Instances: 1000% % Two datasets are provided. the original dataset, in the form provided% by Prof. Hofmann, contains categorical/symbolic attributes and% is in the file "german.data". % % For algorithms that need numerical attributes, Strathclyde University % produced the file "german.data-numeric". This file has been edited % and several indicator variables added to make it suitable for % algorithms which cannot cope with categorical variables. Several% attributes that are ordered categorical (such as attribute 17) have% been coded as integer. This was the form used by StatLog.% % % 6. Number of Attributes german: 20 (7 numerical, 13 categorical)% Number of Attributes german.numer: 24 (24 numerical)% % % 7. Attribute description for german% % Attribute 1: (qualitative)% Status of existing checking account% A11 : ... < 0 DM% A12 : 0 <= ... < 200 DM% A13 : ... >= 200 DM /% salary assignments for at least 1 year% A14 : no checking account% % Attribute 2: (numerical)% Duration in month% % Attribute 3: (qualitative)% Credit history% A30 : no credits taken/% all credits paid back duly% A31 : all credits at this bank paid back duly% A32 : existing credits paid back duly till now% A33 : delay in paying off in the past% A34 : critical account/% other credits existing (not at this bank)% % Attribute 4: (qualitative)% Purpose% A40 : car (new)% A41 : car (used)% A42 : furniture/equipment% A43 : radio/television% A44 : domestic appliances% A45 : repairs% A46 : education% A47 : (vacation - does not exist?)% A48 : retraining% A49 : business% A410 : others% % Attribute 5: (numerical)% Credit amount% % Attibute 6: (qualitative)% Savings account/bonds% A61 : ... < 100 DM% A62 : 100 <= ... < 500 DM% A63 : 500 <= ... < 1000 DM% A64 : .. >= 1000 DM% A65 : unknown/ no savings account% % Attribute 7: (qualitative)% Present employment since% A71 : unemployed% A72 : ... < 1 year% A73 : 1 <= ... < 4 years % A74 : 4 <= ... < 7 years% A75 : .. >= 7 years% % Attribute 8: (numerical)% Installment rate in percentage of disposable income% % Attribute 9: (qualitative)% Personal status and sex% A91 : male : divorced/separated% A92 : female : divorced/separated/married% A93 : male : single% A94 : male : married/widowed% A95 : female : single% % Attribute 10: (qualitative)% Other debtors / guarantors% A101 : none% A102 : co-applicant% A103 : guarantor% % Attribute 11: (numerical)% Present residence since% % Attribute 12: (qualitative)% Property% A121 : real estate% A122 : if not A121 : building society savings agreement/% life insurance% A123 : if not A121/A122 : car or other, not in attribute 6% A124 : unknown / no property% % Attribute 13: (numerical)% Age in years% % Attribute 14: (qualitative)% Other installment plans % A141 : bank% A142 : stores% A143 : none% % Attribute 15: (qualitative)% Housing% A151 : rent% A152 : own% A153 : for free% % Attribute 16: (numerical)% Number of existing credits at this bank%
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