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Regression Analysis with Python

You're reading from   Regression Analysis with Python Discover everything you need to know about the art of regression analysis with Python, and change how you view data

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Product type Paperback
Published in Feb 2016
Publisher
ISBN-13 9781785286315
Length 312 pages
Edition 1st Edition
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Authors (2):
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Luca Massaron Luca Massaron
Author Profile Icon Luca Massaron
Luca Massaron
Alberto Boschetti Alberto Boschetti
Author Profile Icon Alberto Boschetti
Alberto Boschetti
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Table of Contents (11) Chapters Close

Preface 1. Regression – The Workhorse of Data Science 2. Approaching Simple Linear Regression FREE CHAPTER 3. Multiple Regression in Action 4. Logistic Regression 5. Data Preparation 6. Achieving Generalization 7. Online and Batch Learning 8. Advanced Regression Methods 9. Real-world Applications for Regression Models Index

Chapter 4. Logistic Regression

In this chapter, another supervised method is introduced: classification. We will introduce the simplest classifier, the Logistic Regressor, which shares the same foundations as the Linear Regressor, but it targets classification problems.

In the following chapter, you'll find:

  • A formal and mathematical definition of the classification problem, for both binary and multiclass problems
  • How to evaluate classifier performances—that is, their metrics
  • The math behind Logistic Regression
  • A revisited formula for SGD, specifically built for Logistic Regression
  • The multiclass case, with Multiclass Logistic Regression
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