from pyspark.ml.classification import RandomForestClassifier from pyspark.ml.tuning import ParamGridBuilder # Initialize the RandomForestClassifier model rf = RandomForestClassifier() # Define the parameter grid param_grid = ParamGridBuilder() \ .addGrid(rf.maxDepth, [5, 10, 15]) \ .addGrid(rf.numTrees, [10, 20, 30]) \ .build()
from pyspark.ml.classification import LogisticRegression from pyspark.ml.tuning import ParamGridBuilder # Initialize the LogisticRegression model lr = LogisticRegression() # Define the parameter grid param_grid = ParamGridBuilder() \ .addGrid(lr.regParam, [0.01, 0.1, 1.0]) \ .addGrid(lr.elasticNetParam, [0.0, 0.5, 1.0]) \ .build()The PySpark package library used for these examples is pyspark.ml.tuning.