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You're reading from Apache Spark 2.x Machine Learning Cookbook

Product type Book

Published in Sep 2017

Publisher Packt

ISBN-13 9781783551606

Pages 666 pages

Edition 1st Edition

Languages

Scala

Concepts

Machine Learning

Authors (5):

Mohammed Guller

Siamak Amirghodsi

Shuen Mei

Meenakshi Rajendran

Broderick Hall

View More author details

Table of Contents (20) Chapters

Title Page

Credits

About the Authors

About the Reviewer

www.PacktPub.com

Customer Feedback

Preface

1. Practical Machine Learning with Spark Using Scala

2. Just Enough Linear Algebra for Machine Learning with Spark

3. Spark's Three Data Musketeers for Machine Learning - Perfect Together

4. Common Recipes for Implementing a Robust Machine Learning System

5. Practical Machine Learning with Regression and Classification in Spark 2.0 - Part I

6. Practical Machine Learning with Regression and Classification in Spark 2.0 - Part II

7. Recommendation Engine that Scales with Spark

8. Unsupervised Clustering with Apache Spark 2.0

9. Optimization - Going Down the Hill with Gradient Descent

10. Building Machine Learning Systems with Decision Tree and Ensemble Models

11. Curse of High-Dimensionality in Big Data

12. Implementing Text Analytics with Spark 2.0 ML Library

13. Spark Streaming and Machine Learning Library

Solving regression problems with Gradient Boosted Trees (GBT) in Spark 2.0

This recipe is similar to the GBT problem, but we will use regression instead. We will use BoostingStrategy.defaultParams() to direct the GBT to regression:

algo = "Regression"
val boostingStrategy = BoostingStrategy.defaultParams(algo)

How to do it...

Start a new project in IntelliJ or in an IDE of your choice. Make sure the necessary JAR files are included.

Set up the package location where the program will reside:

package spark.ml.cookbook.chapter10.

Import the necessary packages for the Spark context:

import org.apache.spark.mllib.evaluation.RegressionMetrics
import org.apache.spark.mllib.linalg.Vectors
import org.apache.spark.mllib.regression.LabeledPoint
import org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
import org.apache.spark.rdd.RDD
import org.apache.spark.mllib.tree.GradientBoostedTrees
import org.apache.spark.mllib.tree.configuration.BoostingStrategy

import org.apache.spark.sql.SparkSession...