Book Image

MATLAB for Machine Learning - Second Edition

By : Giuseppe Ciaburro
Book Image

MATLAB for Machine Learning - Second Edition

By: Giuseppe Ciaburro

Overview of this book

Discover why the MATLAB programming environment is highly favored by researchers and math experts for machine learning with this guide which is designed to enhance your proficiency in both machine learning and deep learning using MATLAB, paving the way for advanced applications. By navigating the versatile machine learning tools in the MATLAB environment, you’ll learn how to seamlessly interact with the workspace. You’ll then move on to data cleansing, data mining, and analyzing various types of data in machine learning, and visualize data values on a graph. As you progress, you’ll explore various classification and regression techniques, skillfully applying them with MATLAB functions. This book teaches you the essentials of neural networks, guiding you through data fitting, pattern recognition, and cluster analysis. You’ll also explore feature selection and extraction techniques for performance improvement through dimensionality reduction. Finally, you’ll leverage MATLAB tools for deep learning and managing convolutional neural networks. By the end of the book, you’ll be able to put it all together by applying major machine learning algorithms in real-world scenarios.
Table of Contents (17 chapters)
Free Chapter
1
Part 1: Getting Started with Matlab
4
Part 2: Understanding Machine Learning Algorithms in MATLAB
9
Part 3: Machine Learning in Practice

Prediction Using Classification and Regression

Classification algorithms return accurate predictions based on our observations. Starting from a set of predefined class labels, the classifier assigns each piece of input data a class label according to the training model. Classification algorithms learn linear or non-linear associations between independent and categorical dependent variables. For example, a classification algorithm may learn to predict the weather as clear sky, gentle showers or heavy rain, and so on. Regression relates a set of independent variables to a dependent variable, numeric or continuous, for example, predicting rainfall in units of millimeters. Through this technique, it is possible to understand how the value of the dependent variable changes as the independent variable varies. This chapter shows us how to classify an object using nearest neighbors and how to perform an accurate regression analysis in a MATLAB environment. The aim of this chapter is to provide...