January 2018
Intermediate to advanced
470 pages
11h 9m
English
Content preview from Scala Machine Learning Projects
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Model training and hyperparameter tuning
Once we have rowRDD and the header, the next task is to construct the rows of our Schema DataFrame from the variants using the header and rowRDD:
val sqlContext = spark.sqlContextval schemaDF = sqlContext.createDataFrame(rowRDD, header)schemaDF.printSchema()schemaDF.show(10)>>>
Figure 15: A snapshot of the training dataset containing features and the label (that is, Region) columns
In the preceding DataFrame, only a few columns, including the label, are shown so that it fits on the page.
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