Introduction and Implementation of Machine Learning Algorithms in R

View Sample PDF

Author(s): S. R. Mani Sekhar (M. S. Ramaiah Institute of Technology, India)and G. M. Siddesh (M. S. Ramaiah Institute of Technology, India)
Copyright: 2019
Pages: 22
Source title: Sentiment Analysis and Knowledge Discovery in Contemporary Business
Source Author(s)/Editor(s): Dharmendra Singh Rajput (VIT University, India), Ramjeevan Singh Thakur (Maulana Azad National Institute of Technology, India)and S. Muzamil Basha (VIT University, India)
DOI: 10.4018/978-1-5225-4999-4.ch008

Keywords: Business and Organizational Research / Business Science Reference / Knowledge Discovery / Library & Information Science

Purchase

View Introduction and Implementation of Machine Learning Algorithms in R on the publisher's website for pricing and purchasing information.

Abstract

Machine learning is one of the important areas in the field of computer science. It helps to provide an optimized solution for the real-world problems by using past knowledge or previous experience data. There are different types of machine learning algorithms present in computer science. This chapter provides the overview of some selected machine learning algorithms such as linear regression, linear discriminant analysis, support vector machine, naive Bayes classifier, neural networks, and decision trees. Each of these methods is illustrated in detail with an example and R code, which in turn assists the reader to generate their own solutions for the given problems.

The IRMA Community

Research IRM

Introduction and Implementation of Machine Learning Algorithms in R

Purchase

Abstract

Related Content

IRMA Sponsors