July 2018
Intermediate to advanced
334 pages
8h 20m
English
Content preview from Modern Scala Projects
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Step 3 – training the Random Forest classifier
Next, we will split our existing training set (the one used to train the model) into two:
- Validation set: This is a subset of the training dataset which is used to get a preliminary estimate of the effectiveness of the level of skillfulness attained by the model.
- Training set: A training set is that percentage of dataset that the model learns from. This learning process is called training the model. Also because the model learns from this data, the data is said fit the model.
We can accomplish a split by creating an instance of the TrainValidationSplit algorithm:
val validatedTestResults: DataFrame = new TrainValidationSplit() .setSeed(1234567L) .setEstimatorParamMaps(finalParamGrid) .setEstimator(irisPipeline) ...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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