Credit Scoring Model Using Data Mining Techniques a pragmatic approach - Mukherjee, Aroop
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Credit Scoring Model Using Data Mining Techniques a pragmatic approach is a book on credit scores and its implementation using data mining. The credit score plays a vital role where lenders decide in extending you credit. Readers will learn the different aspect of Credit Scoring methods. Chapter I deal with credit scoring and data mining methodology. It also includes the data mining concept. Further Chapter II deals with credit products, credit scoring systems and benefits of credit scoring application. Chapter III talks about the concepts of data mining operation and its process. Chapter IV…mehr

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Produktbeschreibung
Credit Scoring Model Using Data Mining Techniques a pragmatic approach is a book on credit scores and its implementation using data mining. The credit score plays a vital role where lenders decide in extending you credit. Readers will learn the different aspect of Credit Scoring methods. Chapter I deal with credit scoring and data mining methodology. It also includes the data mining concept. Further Chapter II deals with credit products, credit scoring systems and benefits of credit scoring application. Chapter III talks about the concepts of data mining operation and its process. Chapter IV will discuss about the architecture of data mining and knowledge discovery process, in chapter V it describe about various algorithms of credit scoring and framework of data mining and finally the limitation of credit scoring and data mining is being discuss in chapter VI.
Autorenporträt
Aroop Mukherjee is a resourceful and innovative IT Education professional with a distinguished career of over 15 years. He has training experience in the IT/ITeS and published papers in refereed conferences at international levels. He is currently serving as research associate with Computer Science Department, King Saud University, Riyadh, KSA.