Part 4 Modeling Profitability Instead of Default.txt

Modeling Profitability Instead of Default Modeling Profitability Level as a Continuous Output (Instead of Binary Classification Default/No Default) Introduction Bot your o!n "odel and te forecast based on #ggertopia scores are binary classifications classifications$ $ tey forecast forecast one of %ust t!o outco"es$ outco"es$ � Default� or � No Default& Default&� 'our boss is interested in te idea tat it "igt be preferable instead to "odel and forecast profits and losses as continuous values using a a "ultivariate linear regression "odel on te sa"e si input variables& *is idea as arisen because te ban+ as been revie!ing individual profit and loss nu"bers for eac custo"er over te tree,year period and as "ade an interesting discovery$ so"e defaulting custo"ers carried so "uc debt for so long and paid so "uc interest on it tat tey !ere profitable for te ban+ even toug tey defaulted- Many custo"ers !o see" to ave ris+y spending beaviors are also a"ong te "ost profitable for a lending business& .nd at te opposite etre"ecusto"ers !o al!ays paid off teir cards in full eac "ont never defaulted but !ere not very profitable$ te ban+ barely barely bro+e bro+e even even or even even lost lost "oney "oney on its� safest safest� borro!e borro!ers& rs& 'our boss as+s as+s you to forecast forecast eac applicant applicant� s epected profitabi profitability lity in dollarsbefore deciding !eter or not to issue te" a credit card& e !ants to +no! o! reliable tis type of forecast !ould be$ !at is te range above and belo! te point esti"ate tat !ill be correct 012 of te ti"e3 .ltoug it "igt be possible to co"bine te si inputs in oter !ays in te interests of ti"e and focusing on te +ey learning ob%ectives !e !ill use only a si"ple linear co"bination of te si input variables for Part 4 of tis Pro%ect& ('ou sould not include te #ggertopia 5cores as an input variable)& 6uestion 7 is about te coefficie coefficients nts or or � betas� used to co"bine co"bine te standard standardi8ed i8ed inputs to get te best,fit,line on standardi8ed outputs on te *raining 5et& 9e ten use tose fied betas to "easure te observed residual error of te "odel on te *est 5et& 6uestions : troug ; concern te forecasts on te *est 5et& 6uestions < troug 77 loo+ at te *raining 5et results so tat tey can be co"pared (for possible over,fitting) against te *est 5et =esults& 6uestions 7: troug 74 are about te uncertainty tat re"ains in a ne! individual forecast of profitability& >se te te #cel #cel � Linest� function function on te si si inputs inputs and and profitabil profitability ity output output on te te :11 *raining *raining 5et applican applicants ts to calculate calculate te te coefficient coefficients s (te (te � betas� ) tat tat result result in te best,fit line& 6uestion$ Do you feel prepared to ta+e tis ?ui83 'es

r

6uestion$ 6uestion$ 9at 9at are your values for eac .ge

�

beta� on te te *raining *raining 5et3

'ears at current e"ployer 'ears at current address Inco"e over te past year Current credit card debt Current auto"obile debt &17 &70 ,&1