July 2018
Intermediate to advanced
334 pages
8h 20m
English
Content preview from Modern Scala Projects
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Generating predictions – outliers that represent fraud
We start by transforming the probabilityDensities dataframe from before:
val finalPreds: DataFrame= probabilityDensities.map { probRow => if (probRow.getDouble(0) < broadcastTerm) { 1.0 /* Fraud is flagged here */ } else 0.0 }.toDF("PDF")
Now, let's create a new dataframe with two dataframes—the testing dataframe, and the final predictions dataframe. Drop the "label" column in the testing dataframe and do a cross-join with the finalpreds dataframe. Do not forget to persist the new dataframe with the default storage level (MEMORY_AND_DISK):
val labelAndPredictions: DataFrame = testingDframe.drop("label").crossJoin(finalPreds).cache() println("Label And Predictions: " ) labelAndPredictions.show() ...Become 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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