Book Image

Mastering Scala Machine Learning

By : Alex Kozlov
Book Image

Mastering Scala Machine Learning

By: Alex Kozlov

Overview of this book

Since the advent of object-oriented programming, new technologies related to Big Data are constantly popping up on the market. One such technology is Scala, which is considered to be a successor to Java in the area of Big Data by many, like Java was to C/C++ in the area of distributed programing. This book aims to take your knowledge to next level and help you impart that knowledge to build advanced applications such as social media mining, intelligent news portals, and more. After a quick refresher on functional programming concepts using REPL, you will see some practical examples of setting up the development environment and tinkering with data. We will then explore working with Spark and MLlib using k-means and decision trees. Most of the data that we produce today is unstructured and raw, and you will learn to tackle this type of data with advanced topics such as regression, classification, integration, and working with graph algorithms. Finally, you will discover at how to use Scala to perform complex concept analysis, to monitor model performance, and to build a model repository. By the end of this book, you will have gained expertise in performing Scala machine learning and will be able to build complex machine learning projects using Scala.
Table of Contents (17 chapters)
Mastering Scala Machine Learning
Credits
About the Author
Acknowlegement
www.PacktPub.com
Preface
10
Advanced Model Monitoring
Index

What regression stands for?


While the word classification is intuitively clear, the word regression does not seem to imply a predictor of a continuous label. According to the Webster dictionary, regression is:

"a return to a former or less developed state."

It does also mention a special definition for statistics as a measure of the relation between the mean value of one variable (for example, output) and corresponding values of other variables (for example, time and cost), which is actually correct these days. However, historically, the regression coefficient was meant to signify the hereditability of certain characteristics, such as weight and size, from one generation to another, with the hint of planned gene selection, including humans (http://www.amstat.org/publications/jse/v9n3/stanton.html). More specifically, in 1875, Galton, a cousin of Charles Darwin and an accomplished 19th-century scientist in his own right, which was also widely criticized for the promotion of eugenics, had distributed...