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Apache Spark 2.x Cookbook

You're reading from  Apache Spark 2.x Cookbook

Product type Book
Published in May 2017
Publisher
ISBN-13 9781787127265
Pages 294 pages
Edition 1st Edition
Languages
Author (1):
Rishi Yadav Rishi Yadav
Profile icon Rishi Yadav
Toc

Table of Contents (19) Chapters close

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Getting Started with Apache Spark 2. Developing Applications with Spark 3. Spark SQL 4. Working with External Data Sources 5. Spark Streaming 6. Getting Started with Machine Learning 7. Supervised Learning with MLlib — Regression 8. Supervised Learning with MLlib — Classification 9. Unsupervised Learning 10. Recommendations Using Collaborative Filtering 11. Graph Processing Using GraphX and GraphFrames 12. Optimizations and Performance Tuning

Understanding the cost function


The cost function or loss function is a very important function in machine learning algorithms. Most algorithms have some form of cost function, and the goal is to minimize this. Parameters, which affect cost functions, such as stepSize, are called hyperparameters; they need to be set by hand. Therefore, understanding the whole concept of the cost function is very important.

In this recipe, we are going to analyze the cost function in linear regression. Linear regression is a simple algorithm to understand, and it will help you understand the role of cost functions for even complex algorithms.

Let's go back to linear regression. The goal is to find the best-fitting line so that the mean square of the error would be minimum. Here, we are referring to an error as the difference between the value as per the best-fitting line and the actual value of the response variable of the training dataset.

For a simple case of a single predicate variable, the best-fitting line...

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