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Statistical Application Development with R and Python

You're reading from   Statistical Application Development with R and Python Develop applications using data processing, statistical models, and CART

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Product type Paperback
Published in Aug 2017
Publisher
ISBN-13 9781788621199
Length 432 pages
Edition 2nd Edition
Languages
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Author (1):
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Prabhanjan Narayanachar Tattar Prabhanjan Narayanachar Tattar
Author Profile Icon Prabhanjan Narayanachar Tattar
Prabhanjan Narayanachar Tattar
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Toc

Table of Contents (12) Chapters Close

Preface 1. Data Characteristics FREE CHAPTER 2. Import/Export Data 3. Data Visualization 4. Exploratory Analysis 5. Statistical Inference 6. Linear Regression Analysis 7. Logistic Regression Model 8. Regression Models with Regularization 9. Classification and Regression Trees 10. CART and Beyond Index

Logistic regression for the German credit screening dataset

Millions of applications are made to a bank for a variety of loans! The loan may be a personal loan, home loan, car loan, and so forth. From a bank perspective, loans are an asset for them as obviously the customer pays them interest and over a period of time the bank makes profit. If all the customers promptly pay back their loan amount, all their tenure equated monthly installment (EMI) or the complete amount on preclosure of the principal amount, there is only money to be made.

Unfortunately, it is not always the case that the customers pay back the entire amount. In fact, the fraction of people who do not complete the loan duration may also be very small, say about five percent. However, a bad customer may take away the profits of may be 20 or more customers. In this hypothetical case, the bank eventually makes more losses than profit and this may eventually lead to its own bankruptcy.

Now, a loan application form seeks a lot...

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