Source code for mmlspark.stages.StratifiedRepartition

# Copyright (C) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See LICENSE in project root for information.


import sys
if sys.version >= '3':
    basestring = str

from pyspark.ml.param.shared import *
from pyspark import keyword_only
from pyspark.ml.util import JavaMLReadable, JavaMLWritable
from mmlspark.core.serialize.java_params_patch import *
from pyspark.ml.wrapper import JavaTransformer, JavaEstimator, JavaModel
from pyspark.ml.common import inherit_doc
from mmlspark.core.schema.Utils import *

[docs]@inherit_doc class StratifiedRepartition(ComplexParamsMixin, JavaMLReadable, JavaMLWritable, JavaTransformer): """ Args: labelCol (str): The name of the label column mode (str): Specify equal to repartition with replacement across all labels, specify original to keep the ratios in the original dataset, or specify mixed to use a heuristic (default: mixed) seed (long): random seed (default: 539887434) """ @keyword_only def __init__(self, labelCol=None, mode="mixed", seed=539887434): super(StratifiedRepartition, self).__init__() self._java_obj = self._new_java_obj("com.microsoft.ml.spark.stages.StratifiedRepartition") self.labelCol = Param(self, "labelCol", "labelCol: The name of the label column") self.mode = Param(self, "mode", "mode: Specify equal to repartition with replacement across all labels, specify original to keep the ratios in the original dataset, or specify mixed to use a heuristic (default: mixed)") self._setDefault(mode="mixed") self.seed = Param(self, "seed", "seed: random seed (default: 539887434)") self._setDefault(seed=539887434) if hasattr(self, "_input_kwargs"): kwargs = self._input_kwargs else: kwargs = self.__init__._input_kwargs self.setParams(**kwargs)
[docs] @keyword_only def setParams(self, labelCol=None, mode="mixed", seed=539887434): """ Set the (keyword only) parameters Args: labelCol (str): The name of the label column mode (str): Specify equal to repartition with replacement across all labels, specify original to keep the ratios in the original dataset, or specify mixed to use a heuristic (default: mixed) seed (long): random seed (default: 539887434) """ if hasattr(self, "_input_kwargs"): kwargs = self._input_kwargs else: kwargs = self.__init__._input_kwargs return self._set(**kwargs)
[docs] def setLabelCol(self, value): """ Args: labelCol (str): The name of the label column """ self._set(labelCol=value) return self
[docs] def getLabelCol(self): """ Returns: str: The name of the label column """ return self.getOrDefault(self.labelCol)
[docs] def setMode(self, value): """ Args: mode (str): Specify equal to repartition with replacement across all labels, specify original to keep the ratios in the original dataset, or specify mixed to use a heuristic (default: mixed) """ self._set(mode=value) return self
[docs] def getMode(self): """ Returns: str: Specify equal to repartition with replacement across all labels, specify original to keep the ratios in the original dataset, or specify mixed to use a heuristic (default: mixed) """ return self.getOrDefault(self.mode)
[docs] def setSeed(self, value): """ Args: seed (long): random seed (default: 539887434) """ self._set(seed=value) return self
[docs] def getSeed(self): """ Returns: long: random seed (default: 539887434) """ return self.getOrDefault(self.seed)
[docs] @classmethod def read(cls): """ Returns an MLReader instance for this class. """ return JavaMMLReader(cls)
[docs] @staticmethod def getJavaPackage(): """ Returns package name String. """ return "com.microsoft.ml.spark.stages.StratifiedRepartition"
@staticmethod def _from_java(java_stage): module_name=StratifiedRepartition.__module__ module_name=module_name.rsplit(".", 1)[0] + ".StratifiedRepartition" return from_java(java_stage, module_name)