credit-g.arff

是UCI数据库中的一些有代表性的数据集

% Attribute 17: (qualitative)
% 	      Job
% 	      A171 : unemployed/ unskilled  - non-resident
% 	      A172 : unskilled - resident
% 	      A173 : skilled employee / official
% 	      A174 : management/ self-employed/
% 		     highly qualified employee/ officer
% 
% Attribute 18: (numerical)
% 	      Number of people being liable to provide maintenance for
% 
% Attribute 19: (qualitative)
% 	      Telephone
% 	      A191 : none
% 	      A192 : yes, registered under the customers name
% 
% Attribute 20: (qualitative)
% 	      foreign worker
% 	      A201 : yes
% 	      A202 : no
% 
% 
% 
% 8.  Cost Matrix
% 
% This dataset requires use of a cost matrix (see below)
% 
% 
%       1        2
% ----------------------------
%   1   0        1
% -----------------------
%   2   5        0
% 
% (1 = Good,  2 = Bad)
% 
% the rows represent the actual classification and the columns
% the predicted classification.
% 
% It is worse to class a customer as good when they are bad (5), 
% than it is to class a customer as bad when they are good (1).
% 
%
%
%
%
% Relabeled values in attribute checking_status
%    From: A11                     To: '<0'                
%    From: A12                     To: '0<=X<200'          
%    From: A13                     To: '>=200'             
%    From: A14                     To: 'no checking'       
%
%
% Relabeled values in attribute credit_history
%    From: A30                     To: 'no credits/all paid'
%    From: A31                     To: 'all paid'          
%    From: A32                     To: 'existing paid'     
%    From: A33                     To: 'delayed previously'
%    From: A34                     To: 'critical/other existing credit'
%
%
% Relabeled values in attribute purpose
%    From: A40                     To: 'new car'           
%    From: A41                     To: 'used car'          
%    From: A42                     To: furniture/equipment 
%    From: A43                     To: radio/tv            
%    From: A44                     To: 'domestic appliance'
%    From: A45                     To: repairs             
%    From: A46                     To: education           
%    From: A47                     To: vacation            
%    From: A48                     To: retraining          
%    From: A49                     To: business            
%    From: A410                    To: other               
%
%
% Relabeled values in attribute savings_status
%    From: A61                     To: '<100'              
%    From: A62                     To: '100<=X<500'        
%    From: A63                     To: '500<=X<1000'       
%    From: A64                     To: '>=1000'            
%    From: A65                     To: 'no known savings'  
%
%
% Relabeled values in attribute employment
%    From: A71                     To: unemployed          
%    From: A72                     To: '<1'                
%    From: A73                     To: '1<=X<4'            
%    From: A74                     To: '4<=X<7'            
%    From: A75                     To: '>=7'               
%
%
% Relabeled values in attribute personal_status
%    From: A91                     To: 'male div/sep'      
%    From: A92                     To: 'female div/dep/mar'
%    From: A93                     To: 'male single'       
%    From: A94                     To: 'male mar/wid'      
%    From: A95                     To: 'female single'     
%
%
% Relabeled values in attribute other_parties
%    From: A101                    To: none                
%    From: A102                    To: 'co applicant'      
%    From: A103                    To: guarantor           
%
%
% Relabeled values in attribute property_magnitude
%    From: A121                    To: 'real estate'       
%    From: A122                    To: 'life insurance'    
%    From: A123                    To: car                 
%    From: A124                    To: 'no known property' 
%
%
% Relabeled values in attribute other_payment_plans
%    From: A141                    To: bank                
%    From: A142                    To: stores              
%    From: A143                    To: none                
%
%
% Relabeled values in attribute housing
%    From: A151                    To: rent                
%    From: A152                    To: own                 
%    From: A153                    To: 'for free'          
%
%
% Relabeled values in attribute job
%    From: A171                    To: 'unemp/unskilled non res'
%    From: A172                    To: 'unskilled resident'
%    From: A173                    To: skilled             
%    From: A174                    To: 'high qualif/self emp/mgmt'
%
%
% Relabeled values in attribute own_telephone
%    From: A191                    To: none