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Spark Cookbook

You're reading from   Spark Cookbook With over 60 recipes on Spark, covering Spark Core, Spark SQL, Spark Streaming, MLlib, and GraphX libraries this is the perfect Spark book to always have by your side

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Product type Paperback
Published in Jul 2015
Publisher
ISBN-13 9781783987061
Length 226 pages
Edition 1st Edition
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Author (1):
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Rishi Yadav Rishi Yadav
Author Profile Icon Rishi Yadav
Rishi Yadav
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Table of Contents (14) Chapters Close

Preface 1. Getting Started with Apache Spark 2. Developing Applications with Spark FREE CHAPTER 3. External Data Sources 4. Spark SQL 5. Spark Streaming 6. Getting Started with Machine Learning Using MLlib 7. Supervised Learning with MLlib – Regression 8. Supervised Learning with MLlib – Classification 9. Unsupervised Learning with MLlib 10. Recommender Systems 11. Graph Processing Using GraphX 12. Optimizations and Performance Tuning Index

Understanding cost function


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 that. Parameters, which affect cost function, such as stepSize in the last recipe, need to be set by hand. Therefore, understanding the whole concept of cost function is very important.

In this recipe, we are going to analyze cost function for linear regression. Linear regression is a simple algorithm to understand and it will help readers 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 error is minimum. Here, we are referring error as the difference between the value as per the best-fitting line and the actual value of the response variable for the training dataset.

For a simple case of single predicate variable, the best-fit line can be written as:

This function is also called...

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