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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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Toc

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

Regression Learner App

Previously, we described some MATLAB apps. They make fast and easy what is long and laborious. Some procedures that require the use of many functions are automated by a user-friendly environment. Additionally, we do not have to remember the names of all the functions useful to perform a specific analysis, as the graphical interface provides us with all the features available.

The Regression Learner App leads us into a step-by-step regression analysis. Through this app, import and explore data, select features, specify validation schemes, train models, and evaluate results, will be extremely simple and fast.

We can run automated training to look for the best regression model type, including linear regression models, regression trees, Gauss process regression models, vector support vehicles, and regression tree complexes. To reuse the model with new data or...

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