ParamGridBuilder¶
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class
pyspark.ml.tuning.
ParamGridBuilder
[source]¶ Builder for a param grid used in grid search-based model selection.
>>> from pyspark.ml.classification import LogisticRegression >>> lr = LogisticRegression() >>> output = ParamGridBuilder() \ ... .baseOn({lr.labelCol: 'l'}) \ ... .baseOn([lr.predictionCol, 'p']) \ ... .addGrid(lr.regParam, [1.0, 2.0]) \ ... .addGrid(lr.maxIter, [1, 5]) \ ... .build() >>> expected = [ ... {lr.regParam: 1.0, lr.maxIter: 1, lr.labelCol: 'l', lr.predictionCol: 'p'}, ... {lr.regParam: 2.0, lr.maxIter: 1, lr.labelCol: 'l', lr.predictionCol: 'p'}, ... {lr.regParam: 1.0, lr.maxIter: 5, lr.labelCol: 'l', lr.predictionCol: 'p'}, ... {lr.regParam: 2.0, lr.maxIter: 5, lr.labelCol: 'l', lr.predictionCol: 'p'}] >>> len(output) == len(expected) True >>> all([m in expected for m in output]) True
New in version 1.4.0.
Methods
Methods Documentation
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addGrid
(param, values)[source]¶ Sets the given parameters in this grid to fixed values.
param must be an instance of Param associated with an instance of Params (such as Estimator or Transformer).
New in version 1.4.0.
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