Book Image

MATLAB for Machine Learning

By : Giuseppe Ciaburro, Pavan Kumar Kolluru
Book Image

MATLAB for Machine Learning

By: Giuseppe Ciaburro, Pavan Kumar Kolluru

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
Credits
Foreword
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
8
Improving the Performance of the Machine Learning Model - Dimensionality Reduction

Chapter 3. From Data to Knowledge Discovery

Modern computer technology, coupled with the availability of more and more powerful sensors, has led to impressive-sized collections of information. Having a lot of data, on one hand, undoubtedly represents an advantage; on the other hand, it is a problem. This is because it imposes obvious management problems, in the sense that more sophisticated tools will be needed to extract knowledge from it.

These pieces of data, taken individually, are in fact pieces of elementary information that describe some particular aspects of a phenomenon, but do not allow us to represent them. To get more knowledge about a phenomenon, a form of analysis is needed that can link the data to some significant aspect of the phenomenon itself. It is therefore necessary to follow a path to transform data into an element of knowledge.

The two important steps in this path are the analysis, which extracts information from the raw data, and the model, which allows the information...