April 2017
Intermediate to advanced
532 pages
12h 39m
English
book
Machine Learning with Spark - Second Edition
by Rajdeep Dua, Brian O'Neill, Stephen Boesch, Manpreet Singh Ghotra, Nick Pentreath
Content preview from Machine Learning with Spark - Second Edition
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Training a classification model on the Kaggle/StumbleUpon evergreen classification dataset
We can now apply the models from Spark ML to our input data. First, we need to import the required classes, and set up some minimal input parameters for each model. For logistic regression and SVM, this is the number of iterations while, for the decision tree model, it is the maximum tree depth.
import org.apache.spark.mllib.classification.LogisticRegressionWithSGD import org.apache.spark.mllib.classification.SVMWithSGD import org.apache.spark.mllib.classification.NaiveBayes import org.apache.spark.mllib.tree.DecisionTree import org.apache.spark.mllib.tree.configuration.Algo import org.apache.spark.mllib.tree.impurity.Entropy val numIterations = 10 ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.