Skip to Content
Java: Data Science Made Easy
book

Java: Data Science Made Easy

by Richard M. Reese, Jennifer L. Reese, Alexey Grigorev
July 2017
Beginner to intermediate
715 pages
17h 3m
English
Packt Publishing
Content preview from Java: Data Science Made Easy

Binary classification models

As we have already discussed, the binary classification model deals with the case when there are only two possible outcomes that we want to predict. Typically, in these settings, we have items of the positive class (the presence of some effect) and items of the negative class (the absence of some effect).  

For example, the positive label can be relevant, duplicate, fail to pay the debts, and so on. The instances of the positive class are typically assigned the target value of 1. Also, we have negative instances, such as not relevant, not duplicate, pays the debts, and they are assigned the target value of 0.

This separation into positive and negative classes is somewhat artificial, and in some cases does not ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Java Data Science Cookbook

Java Data Science Cookbook

Rushdi Shams
Java for Data Science

Java for Data Science

Walter Molina, Richard M. Reese, Shilpi Saxena, Jennifer L. Reese

Publisher Resources

ISBN: 9781788475655Supplemental Content