December 2016
Beginner to intermediate
392 pages
8h 13m
English
Content preview from Apache Spark for Data Science CookbookBecome 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,
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Applying linear regression
In this recipe, we'll see how to apply linear regression.
Getting ready
To step through this recipe, you will need a running Spark cluster in any one of the modes, for instance, local, standalone, YARN, or Mesos. For installing Spark on a standalone cluster, please refer to http://spark.apache.org/docs/latest/spark-standalone.html. Also, include the Spark MLlib package in the build.sbt file so that it downloads the related libraries and the API can be used. Install Hadoop (optionally), Scala, and Java.
How to do it…
- The final step is to convert data into train and test datasets and apply the regression model on the training data:
//Split the data frame into train and test sets val train_Df = final_Df.filter(final_Df("Item_Outlet_Sales").isNotNull) ...
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