pyspark.ml.tuning.
CrossValidatorModel
CrossValidatorModel contains the model with the highest average cross-validation metric across folds and uses this model to transform input data. CrossValidatorModel also tracks the metrics for each param map evaluated.
New in version 1.4.0.
Methods
clear(param)
clear
Clears a param from the param map if it has been explicitly set.
copy([extra])
copy
Creates a copy of this instance with a randomly generated uid and some extra params.
explainParam(param)
explainParam
Explains a single param and returns its name, doc, and optional default value and user-supplied value in a string.
explainParams()
explainParams
Returns the documentation of all params with their optionally default values and user-supplied values.
extractParamMap([extra])
extractParamMap
Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values < user-supplied values < extra.
getEstimator()
getEstimator
Gets the value of estimator or its default value.
getEstimatorParamMaps()
getEstimatorParamMaps
Gets the value of estimatorParamMaps or its default value.
getEvaluator()
getEvaluator
Gets the value of evaluator or its default value.
getFoldCol()
getFoldCol
Gets the value of foldCol or its default value.
getNumFolds()
getNumFolds
Gets the value of numFolds or its default value.
getOrDefault(param)
getOrDefault
Gets the value of a param in the user-supplied param map or its default value.
getParam(paramName)
getParam
Gets a param by its name.
getSeed()
getSeed
Gets the value of seed or its default value.
hasDefault(param)
hasDefault
Checks whether a param has a default value.
hasParam(paramName)
hasParam
Tests whether this instance contains a param with a given (string) name.
isDefined(param)
isDefined
Checks whether a param is explicitly set by user or has a default value.
isSet(param)
isSet
Checks whether a param is explicitly set by user.
load(path)
load
Reads an ML instance from the input path, a shortcut of read().load(path).
read()
read
Returns an MLReader instance for this class.
save(path)
save
Save this ML instance to the given path, a shortcut of ‘write().save(path)’.
set(param, value)
set
Sets a parameter in the embedded param map.
transform(dataset[, params])
transform
Transforms the input dataset with optional parameters.
write()
write
Returns an MLWriter instance for this ML instance.
Attributes
estimator
estimatorParamMaps
evaluator
foldCol
numFolds
params
Returns all params ordered by name.
seed
Methods Documentation
Creates a copy of this instance with a randomly generated uid and some extra params. This copies the underlying bestModel, creates a deep copy of the embedded paramMap, and copies the embedded and extra parameters over. It does not copy the extra Params into the subModels.
Extra parameters to copy to the new instance
Copy of this instance
extra param values
merged param map
New in version 2.0.0.
New in version 3.1.0.
Gets the value of a param in the user-supplied param map or its default value. Raises an error if neither is set.
New in version 2.3.0.
New in version 1.3.0.
pyspark.sql.DataFrame
input dataset
an optional param map that overrides embedded params.
transformed dataset
Attributes Documentation
Returns all params ordered by name. The default implementation uses dir() to get all attributes of type Param.
dir()
Param