DefaultParamsWriter#
- class pyspark.ml.util.DefaultParamsWriter(instance)[source]#
- Specialization of - MLWriterfor- Paramstypes- Class for writing Estimators and Transformers whose parameters are JSON-serializable. - New in version 2.3.0. - Methods - extractJsonParams(instance, skipParams)- option(key, value)- Adds an option to the underlying MLWriter. - Overwrites if the output path already exists. - save(path)- Save the ML instance to the input path. - saveImpl(path)- save() handles overwriting and then calls this method. - saveMetadata(instance, path, sc[, ...])- Saves metadata + Params to: path + "/metadata" - session(sparkSession)- Sets the Spark Session to use for saving/loading. - Attributes - Returns the underlying SparkContext. - Returns the user-specified Spark Session or the default. - Methods Documentation - option(key, value)#
- Adds an option to the underlying MLWriter. See the documentation for the specific model’s writer for possible options. The option name (key) is case-insensitive. 
 - overwrite()#
- Overwrites if the output path already exists. 
 - save(path)#
- Save the ML instance to the input path. 
 - saveImpl(path)[source]#
- save() handles overwriting and then calls this method. Subclasses should override this method to implement the actual saving of the instance. 
 - static saveMetadata(instance, path, sc, extraMetadata=None, paramMap=None)[source]#
- Saves metadata + Params to: path + “/metadata” - class 
- timestamp 
- sparkVersion 
- uid 
- paramMap 
- defaultParamMap (since 2.4.0) 
- (optionally, extra metadata) 
 - Parameters
- extraMetadatadict, optional
- Extra metadata to be saved at same level as uid, paramMap, etc. 
- paramMapdict, optional
- If given, this is saved in the “paramMap” field. 
 
 
 - session(sparkSession)#
- Sets the Spark Session to use for saving/loading. 
 - Attributes Documentation - sc#
- Returns the underlying SparkContext. 
 - sparkSession#
- Returns the user-specified Spark Session or the default.