Год выпуска: 2012 Автор: Ravinder Singh Издательство: LAP Lambert Academic Publishing Страниц: 156 ISBN: 9783659300868
Описание
Credit Scoring studies are very important for any financial house. Both traditional statistical and modern data mining/machine learning tools have been evaluated in the credit scoring problem. Predictive modeling defaulter risk is one of the important problems in credit risk management. There are quite a few aggregate models and data driven models available in literature But very few of the studies facilitate the comparison of majority of the commonly employed tools in single comprehensive study. Additionally no study assesses the performance on more then two data sets and reports the results at the same time. So a macro or a simulator is designed which would work on multiple data sets and make the process of credit scoring transparent to the novice user. In initial stage, tools were compared using Dtreg predictive modeling software. Subsequently a SAS macro is developed to evaluate the effectiveness of tools available in SAS enterprise miner. The results revealed that...
Мариночка! Большое Вам спасибо, я защитилась с оценкой отлично. Мне очень понравилось с Вами работать!!! Буду рекомендовать другим студентам. С Уважением и большой признательностью. Еще раз спасибо!