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The Data Analysis Workshop

You're reading from   The Data Analysis Workshop Solve business problems with state-of-the-art data analysis models, developing expert data analysis skills along the way

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781839211386
Length 626 pages
Edition 1st Edition
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Authors (3):
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Konstantin Palagachev Konstantin Palagachev
Author Profile Icon Konstantin Palagachev
Konstantin Palagachev
Gururajan Govindan Gururajan Govindan
Author Profile Icon Gururajan Govindan
Gururajan Govindan
Shubhangi Hora Shubhangi Hora
Author Profile Icon Shubhangi Hora
Shubhangi Hora
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Table of Contents (12) Chapters Close

Preface
1. Bike Sharing Analysis 2. Absenteeism at Work FREE CHAPTER 3. Analyzing Bank Marketing Campaign Data 4. Tackling Company Bankruptcy 5. Analyzing the Online Shopper's Purchasing Intention 6. Analysis of Credit Card Defaulters 7. Analyzing the Heart Disease Dataset 8. Analyzing Online Retail II Dataset 9. Analysis of the Energy Consumed by Appliances 10. Analyzing Air Quality Appendix

Modeling the Relationship via Logistic Regression

We will dedicate the rest of this chapter to one of the fundamental techniques in data analysis and machine learning: linear and logistic regression.

Suppose that we are estimating the relationship between m different features.

In both linear and logistic regression, a set of features, X1, ..., Xm, and a target variable, Y, are provided to model the target variable, Y, as a function of the features, X1, ..., Xm, as in the following equation:

Figure 3.16: General form of linear/logistic regression

Figure 3.16: General form of linear/logistic regression

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