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Showing content from https://api-docs.databricks.com/python/pyspark/latest/api/pyspark.ml.PipelineModel.html below:

PipelineModel — PySpark master documentation

class pyspark.ml.PipelineModel(stages: List[pyspark.ml.base.Transformer])¶

Represents a compiled pipeline with transformers and fitted models.

Methods

clear(param)

Clears a param from the param map if it has been explicitly set.

copy([extra])

Creates a copy of this instance.

explainParam(param)

Explains a single param and returns its name, doc, and optional default value and user-supplied value in a string.

explainParams()

Returns the documentation of all params with their optionally default values and user-supplied values.

extractParamMap([extra])

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.

getOrDefault(param)

Gets the value of a param in the user-supplied param map or its default value.

getParam(paramName)

Gets a param by its name.

hasDefault(param)

Checks whether a param has a default value.

hasParam(paramName)

Tests whether this instance contains a param with a given (string) name.

isDefined(param)

Checks whether a param is explicitly set by user or has a default value.

isSet(param)

Checks whether a param is explicitly set by user.

load(path)

Reads an ML instance from the input path, a shortcut of read().load(path).

read()

Returns an MLReader instance for this class.

save(path)

Save this ML instance to the given path, a shortcut of ‘write().save(path)’.

set(param, value)

Sets a parameter in the embedded param map.

transform(dataset[, params])

Transforms the input dataset with optional parameters.

write()

Returns an MLWriter instance for this ML instance.

Attributes

params

Returns all params ordered by name.

Methods Documentation

clear(param: pyspark.ml.param.Param) → None¶

Clears a param from the param map if it has been explicitly set.

copy(extra: Optional[ParamMap] = None) → PipelineModel¶

Creates a copy of this instance.

Parameters

extra – extra parameters

Returns

new instance

explainParam(param: Union[str, pyspark.ml.param.Param]) → str¶

Explains a single param and returns its name, doc, and optional default value and user-supplied value in a string.

explainParams() → str¶

Returns the documentation of all params with their optionally default values and user-supplied values.

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.

Parameters

extradict, optional

extra param values

Returns

dict

merged param map

getOrDefault(param: Union[str, pyspark.ml.param.Param[T]]) → Union[Any, T]¶

Gets the value of a param in the user-supplied param map or its default value. Raises an error if neither is set.

getParam(paramName: str) → pyspark.ml.param.Param¶

Gets a param by its name.

hasDefault(param: Union[str, pyspark.ml.param.Param[Any]]) → bool¶

Checks whether a param has a default value.

hasParam(paramName: str) → bool¶

Tests whether this instance contains a param with a given (string) name.

isDefined(param: Union[str, pyspark.ml.param.Param[Any]]) → bool¶

Checks whether a param is explicitly set by user or has a default value.

isSet(param: Union[str, pyspark.ml.param.Param[Any]]) → bool¶

Checks whether a param is explicitly set by user.

classmethod load(path: str) → RL¶

Reads an ML instance from the input path, a shortcut of read().load(path).

classmethod read() → pyspark.ml.pipeline.PipelineModelReader¶

Returns an MLReader instance for this class.

save(path: str) → None¶

Save this ML instance to the given path, a shortcut of ‘write().save(path)’.

set(param: pyspark.ml.param.Param, value: Any) → None¶

Sets a parameter in the embedded param map.

transform(dataset: pyspark.sql.dataframe.DataFrame, params: Optional[ParamMap] = None) → pyspark.sql.dataframe.DataFrame¶

Transforms the input dataset with optional parameters.

Parameters

datasetpyspark.sql.DataFrame

input dataset

paramsdict, optional

an optional param map that overrides embedded params.

Returns

pyspark.sql.DataFrame

transformed dataset

write() → pyspark.ml.util.MLWriter¶

Returns an MLWriter instance for this ML instance.

Attributes Documentation

params¶

Returns all params ordered by name. The default implementation uses dir() to get all attributes of type Param.

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