RankingTrainValidationSplit¶
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class
RankingTrainValidationSplit.
RankingTrainValidationSplit
(estimator=None, estimatorParamMaps=None, evaluator=None, seed=None)[source]¶ Bases:
pyspark.ml.base.Estimator
,pyspark.ml.tuning.ValidatorParams
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copy
(extra=None)[source]¶ Creates a copy of this instance with a randomly generated uid and some extra params. This copies creates a deep copy of the embedded paramMap, and copies the embedded and extra parameters over.
Parameters: extra – Extra parameters to copy to the new instance Returns: Copy of this instance
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getItemCol
()[source]¶ Returns: column name for item ids. Ids must be within the integer value range. (default: item) Return type: str
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getUserCol
()[source]¶ Returns: column name for user ids. Ids must be within the integer value range. (default: user) Return type: str
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itemCol
= Param(parent='undefined', name='itemCol', doc='itemCol: column name for item ids. Ids must be within the integer value range. (default: item)')¶
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ratingCol
= Param(parent='undefined', name='ratingCol', doc='ratingCol: column name for ratings (default: rating)')¶
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setItemCol
(value)[source]¶ Parameters: itemCol (str) – column name for item ids. Ids must be within the integer value range. (default: item)
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setParams
(estimator=None, estimatorParamMaps=None, evaluator=None, seed=None)[source]¶ setParams(self, estimator=None, estimatorParamMaps=None, evaluator=None, numFolds=3, seed=None): Sets params for cross validator.
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setTrainRatio
(value)[source]¶ Sets the value of
trainRatio
.
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setUserCol
(value)[source]¶ Parameters: userCol (str) – column name for user ids. Ids must be within the integer value range. (default: user)
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trainRatio
= Param(parent='undefined', name='trainRatio', doc='Param for ratio between train and validation data. Must be between 0 and 1.')¶
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userCol
= Param(parent='undefined', name='userCol', doc='userCol: column name for user ids. Ids must be within the integer value range. (default: user)')¶
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