Source code for mmlspark.recommendation.RankingAdapterModel

# 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 *
from mmlspark.core.schema.TypeConversionUtils import generateTypeConverter, complexTypeConverter

[docs]@inherit_doc class RankingAdapterModel(ComplexParamsMixin, JavaMLReadable, JavaMLWritable, JavaTransformer): """ Args: itemCol (str): Column of items k (int): number of items (default: 10) labelCol (str): The name of the label column (default: label) minRatingsPerItem (int): min ratings for items > 0 (default: 1) minRatingsPerUser (int): min ratings for users > 0 (default: 1) mode (str): recommendation mode (default: allUsers) ratingCol (str): Column of ratings recommender (object): estimator for selection recommenderModel (object): recommenderModel userCol (str): Column of users """ @keyword_only def __init__(self, itemCol=None, k=10, labelCol="label", minRatingsPerItem=1, minRatingsPerUser=1, mode="allUsers", ratingCol=None, recommender=None, recommenderModel=None, userCol=None): super(RankingAdapterModel, self).__init__() self._java_obj = self._new_java_obj("com.microsoft.ml.spark.recommendation.RankingAdapterModel") self._cache = {} self.itemCol = Param(self, "itemCol", "itemCol: Column of items") self.k = Param(self, "k", "k: number of items (default: 10)") self._setDefault(k=10) self.labelCol = Param(self, "labelCol", "labelCol: The name of the label column (default: label)") self._setDefault(labelCol="label") self.minRatingsPerItem = Param(self, "minRatingsPerItem", "minRatingsPerItem: min ratings for items > 0 (default: 1)") self._setDefault(minRatingsPerItem=1) self.minRatingsPerUser = Param(self, "minRatingsPerUser", "minRatingsPerUser: min ratings for users > 0 (default: 1)") self._setDefault(minRatingsPerUser=1) self.mode = Param(self, "mode", "mode: recommendation mode (default: allUsers)") self._setDefault(mode="allUsers") self.ratingCol = Param(self, "ratingCol", "ratingCol: Column of ratings") self.recommender = Param(self, "recommender", "recommender: estimator for selection", generateTypeConverter("recommender", self._cache, complexTypeConverter)) self.recommenderModel = Param(self, "recommenderModel", "recommenderModel: recommenderModel", generateTypeConverter("recommenderModel", self._cache, complexTypeConverter)) self.userCol = Param(self, "userCol", "userCol: Column of users") if hasattr(self, "_input_kwargs"): kwargs = self._input_kwargs else: kwargs = self.__init__._input_kwargs self.setParams(**kwargs)
[docs] @keyword_only def setParams(self, itemCol=None, k=10, labelCol="label", minRatingsPerItem=1, minRatingsPerUser=1, mode="allUsers", ratingCol=None, recommender=None, recommenderModel=None, userCol=None): """ Set the (keyword only) parameters Args: itemCol (str): Column of items k (int): number of items (default: 10) labelCol (str): The name of the label column (default: label) minRatingsPerItem (int): min ratings for items > 0 (default: 1) minRatingsPerUser (int): min ratings for users > 0 (default: 1) mode (str): recommendation mode (default: allUsers) ratingCol (str): Column of ratings recommender (object): estimator for selection recommenderModel (object): recommenderModel userCol (str): Column of users """ if hasattr(self, "_input_kwargs"): kwargs = self._input_kwargs else: kwargs = self.__init__._input_kwargs return self._set(**kwargs)
[docs] def setItemCol(self, value): """ Args: itemCol (str): Column of items """ self._set(itemCol=value) return self
[docs] def getItemCol(self): """ Returns: str: Column of items """ return self.getOrDefault(self.itemCol)
[docs] def setK(self, value): """ Args: k (int): number of items (default: 10) """ self._set(k=value) return self
[docs] def getK(self): """ Returns: int: number of items (default: 10) """ return self.getOrDefault(self.k)
[docs] def setLabelCol(self, value): """ Args: labelCol (str): The name of the label column (default: label) """ self._set(labelCol=value) return self
[docs] def getLabelCol(self): """ Returns: str: The name of the label column (default: label) """ return self.getOrDefault(self.labelCol)
[docs] def setMinRatingsPerItem(self, value): """ Args: minRatingsPerItem (int): min ratings for items > 0 (default: 1) """ self._set(minRatingsPerItem=value) return self
[docs] def getMinRatingsPerItem(self): """ Returns: int: min ratings for items > 0 (default: 1) """ return self.getOrDefault(self.minRatingsPerItem)
[docs] def setMinRatingsPerUser(self, value): """ Args: minRatingsPerUser (int): min ratings for users > 0 (default: 1) """ self._set(minRatingsPerUser=value) return self
[docs] def getMinRatingsPerUser(self): """ Returns: int: min ratings for users > 0 (default: 1) """ return self.getOrDefault(self.minRatingsPerUser)
[docs] def setMode(self, value): """ Args: mode (str): recommendation mode (default: allUsers) """ self._set(mode=value) return self
[docs] def getMode(self): """ Returns: str: recommendation mode (default: allUsers) """ return self.getOrDefault(self.mode)
[docs] def setRatingCol(self, value): """ Args: ratingCol (str): Column of ratings """ self._set(ratingCol=value) return self
[docs] def getRatingCol(self): """ Returns: str: Column of ratings """ return self.getOrDefault(self.ratingCol)
[docs] def setRecommender(self, value): """ Args: recommender (object): estimator for selection """ self._set(recommender=value) return self
[docs] def getRecommender(self): """ Returns: object: estimator for selection """ return self._cache.get("recommender", None)
[docs] def setRecommenderModel(self, value): """ Args: recommenderModel (object): recommenderModel """ self._set(recommenderModel=value) return self
[docs] def getRecommenderModel(self): """ Returns: object: recommenderModel """ return self._cache.get("recommenderModel", None)
[docs] def setUserCol(self, value): """ Args: userCol (str): Column of users """ self._set(userCol=value) return self
[docs] def getUserCol(self): """ Returns: str: Column of users """ return self.getOrDefault(self.userCol)
[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.recommendation.RankingAdapterModel"
@staticmethod def _from_java(java_stage): module_name=RankingAdapterModel.__module__ module_name=module_name.rsplit(".", 1)[0] + ".RankingAdapterModel" return from_java(java_stage, module_name)