Readme.txt

This file contains the instructions on how to execute the code properly.

1. Please save dataset file (SouthGermanCredit.asc) in the same folder as Jupiter Notebook coding file (assignment2.ipynb)

2. Below is additional information from original source to interpret columns' label from German to English and meaning behind values recorded in each columns:

	$`laufkont = status`
                                               
 	1 : no checking account                       
 	2 : ... < 0 DM                                
 	3 : 0<= ... < 200 DM                          
 	4 : ... >= 200 DM / salary for at least 1 year

	$`laufzeit = duration`
     

	$`moral = credit_history`
                                                
 	0 : delay in paying off in the past            
 	1 : critical account/other credits elsewhere   
 	2 : no credits taken/all credits paid back duly
 	3 : existing credits paid back duly till now   
 	4 : all credits at this bank paid back duly    

	$`verw = purpose`
                        
	0 : others             
 	1 : car (new)          
 	2 : car (used)         
 	3 : furniture/equipment
 	4 : radio/television   
 	5 : domestic appliances
 	6 : repairs            
 	7 : education          
 	8 : vacation           
 	9 : retraining         
 	10 : business          

	$`hoehe = amount`
     

	$`sparkont = savings`
                               
	1 : unknown/no savings account
 	2 : ... <  100 DM             
 	3 : 100 <= ... <  500 DM      
 	4 : 500 <= ... < 1000 DM      
 	5 : ... >= 1000 DM            

	$`beszeit = employment_duration`
                     
 	1 : unemployed      
 	2 : < 1 yr          
 	3 : 1 <= ... < 4 yrs
 	4 : 4 <= ... < 7 yrs
 	5 : >= 7 yrs        

	$`rate = installment_rate`
                   
 	1 : >= 35         
 	2 : 25 <= ... < 35
 	3 : 20 <= ... < 25
 	4 : < 20          

	$`famges = personal_status_sex`
                                         
 	1 : male : divorced/separated           
 	2 : female : non-single or male : single
 	3 : male : married/widowed              
 	4 : female : single                     

	$`buerge = other_debtors`
                 
 	1 : none        
 	2 : co-applicant
 	3 : guarantor   

	$`wohnzeit = present_residence`
                     
 	1 : < 1 yr          
 	2 : 1 <= ... < 4 yrs
 	3 : 4 <= ... < 7 yrs
 	4 : >= 7 yrs        

	$`verm = property`
                                              
 	1 : unknown / no property                    
 	2 : car or other                             
 	3 : building soc. savings agr./life insurance
 	4 : real estate                              

	$`alter = age`
     

	$`weitkred = other_installment_plans`
           
	1 : bank  
 	2 : stores
 	3 : none  

	$`wohn = housing`
             
 	1 : for free
 	2 : rent    
 	3 : own     

	$`bishkred = number_credits`
         
 	1 : 1   
 	2 : 2-3 
 	3 : 4-5 
 	4 : >= 6

	$`beruf = job`
                                               
 	1 : unemployed/unskilled - non-resident       
 	2 : unskilled - resident                      
 	3 : skilled employee/official                 
 	4 : manager/self-empl./highly qualif. employee

	$`pers = people_liable`
              
 	1 : 3 or more
 	2 : 0 to 2   

	$`telef = telephone`
                              
 	1 : no                       
 	2 : yes (under customer name)

	$`gastarb = foreign_worker`
        
 	1 : yes
 	2 : no 

	$`kredit = credit_risk`
 	        
 	0 : bad 
 	1 : good

3. In case if the code has not run in Jupyter Notebook, please go to Kernel and click "Restart & Run All" to execute all the code.