Book Image

MATLAB for Machine Learning

By : Giuseppe Ciaburro
Book Image

MATLAB for Machine Learning

By: Giuseppe Ciaburro

Overview of this book

MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners. You’ll start by getting your system ready with t he MATLAB environment for machine learning and you’ll see how to easily interact with the Matlab workspace. We’ll then move on to data cleansing, mining and analyzing various data types in machine learning and you’ll see how to display data values on a plot. Next, you’ll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You’ll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you’ll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB.
Table of Contents (17 chapters)
Title Page
About the Author
About the Reviewers
Customer Feedback
Improving the Performance of the Machine Learning Model - Dimensionality Reduction

Exploratory statistics - numerical measures

In the exploratory phase of a study, we try to gather a first set of information needed to derive features that can guide us in choosing the right tools to extract knowledge from the data. Those analyses provide a variety of tools for quickly summarizing and gaining insight about a set of data. The purpose of exploratory analysis is to use statistical indicator and visualizations to better understand the data, find clues about data trends and its quality, and formulate hypotheses from our analysis. We do not want to make imaginative or aesthetically pleasing views to surprise the interlocutor; our goal is to try to answer specific questions through data analysis.

Measures of location

The first step in our analysis is to estimate a localization parameter for distribution; that is, to find a typical or central value that best describes the data. MATLAB provides several methods and techniques to execute an effective measure of central tendency through...