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MATLAB for Machine Learning

You're reading from   MATLAB for Machine Learning Practical examples of regression, clustering and neural networks

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Product type Paperback
Published in Aug 2017
Publisher Packt
ISBN-13 9781788398435
Length 382 pages
Edition 1st Edition
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Authors (2):
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Pavan Kumar Kolluru Pavan Kumar Kolluru
Author Profile Icon Pavan Kumar Kolluru
Pavan Kumar Kolluru
Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
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Table of Contents (10) Chapters Close

Preface 1. Getting Started with MATLAB Machine Learning FREE CHAPTER 2. Importing and Organizing Data in MATLAB 3. From Data to Knowledge Discovery 4. Finding Relationships between Variables - Regression Techniques 5. Pattern Recognition through Classification Algorithms 6. Identifying Groups of Data Using Clustering Methods 7. Simulation of Human Thinking - Artificial Neural Networks 8. Improving the Performance of the Machine Learning Model - Dimensionality Reduction 9. Machine Learning in Practice

Finding Relationships between Variables - Regression Techniques

Regression analysis is a statistical process of studying the relationship between a set of independent variables (explanatory variables) and the dependent variable (response variable). Through this technique, it is possible to understand how the value of the response variable changes when the explanatory variable is varied.

Consider a group of bikers about which some information has been collected: number of years of use, number of kilometers traveled in one year, and number of falls. Through these techniques, we can find that on an average, when the number of kilometers traveled increases, the number of falls also increases. By increasing the number of years of motorcycle usage and so increasing the experience, the number of falls tends to decrease.

A regression analysis can be conducted for a dual purpose:

  • Explanatory...
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