Book Image

Machine Learning with Scala Quick Start Guide

By : Md. Rezaul Karim, Ajay Kumar N
Book Image

Machine Learning with Scala Quick Start Guide

By: Md. Rezaul Karim, Ajay Kumar N

Overview of this book

Scala is a highly scalable integration of object-oriented nature and functional programming concepts that make it easy to build scalable and complex big data applications. This book is a handy guide for machine learning developers and data scientists who want to develop and train effective machine learning models in Scala. The book starts with an introduction to machine learning, while covering deep learning and machine learning basics. It then explains how to use Scala-based ML libraries to solve classification and regression problems using linear regression, generalized linear regression, logistic regression, support vector machine, and Naïve Bayes algorithms. It also covers tree-based ensemble techniques for solving both classification and regression problems. Moving ahead, it covers unsupervised learning techniques, such as dimensionality reduction, clustering, and recommender systems. Finally, it provides a brief overview of deep learning using a real-life example in Scala.
Table of Contents (9 chapters)

Scala for Learning Classification

In the previous chapter, we saw how to develop a predictive model for analyzing insurance severity claims as a regression analysis problem. We applied very simple linear regression, as well as generalized linear regression (GLR).

In this chapter, we'll learn about another supervised learning task, called classification. We'll use widely used algorithms such as logistic regression, Naive Bayes (NB), and Support Vector Machines (SVMs) to analyze and predict whether a customer is likely to cancel the subscription of their telecommunication contract or not.

In particular, we will cover the following topics:

  • Introduction to classification
  • Learning classification with a real-life example
  • Logistic regression for churn prediction
  • SVM for churn prediction
  • NB for prediction