Book Image

R Machine Learning By Example

By : Raghav Bali
Book Image

R Machine Learning By Example

By: Raghav Bali

Overview of this book

Data science and machine learning are some of the top buzzwords in the technical world today. From retail stores to Fortune 500 companies, everyone is working hard to making machine learning give them data-driven insights to grow their business. With powerful data manipulation features, machine learning packages, and an active developer community, R empowers users to build sophisticated machine learning systems to solve real-world data problems. This book takes you on a data-driven journey that starts with the very basics of R and machine learning and gradually builds upon the concepts to work on projects that tackle real-world problems. You’ll begin by getting an understanding of the core concepts and definitions required to appreciate machine learning algorithms and concepts. Building upon the basics, you will then work on three different projects to apply the concepts of machine learning, following current trends and cover major algorithms as well as popular R packages in detail. These projects have been neatly divided into six different chapters covering the worlds of e-commerce, finance, and social-media, which are at the very core of this data-driven revolution. Each of the projects will help you to understand, explore, visualize, and derive insights depending upon the domain and algorithms. Through this book, you will learn to apply the concepts of machine learning to deal with data-related problems and solve them using the powerful yet simple language, R.
Table of Contents (15 chapters)
R Machine Learning By Example
About the Authors
About the Reviewer

Evaluating a product contingency matrix

We will be doing a couple of things here. First, we will analyze a small toy dataset belonging to a supermarket, by using a product contingency matrix of product pair purchases based on their frequency. Then we will move on to contingency matrices based on other metrics such as support, lift, and so on by using another dataset.

The data for our first matrix consists of the six most popular products sold at the supermarket and also the number of times each product was sold by itself and in combination with the other products. We have the data in the form of a data table captured in a csv file, as you can see in the following figure:

To analyze this data, we first need to understand what it depicts. Basically, each cell value denotes the number of times that product combination was sold. Thus, the cell combination (1, A) denotes the product combination (milk, milk), which is basically the number of times milk was bought. Another example is the cell combination...