RankingEvaluator¶

class RankingEvaluator.RankingEvaluator(rawPredictionCol='rawPrediction', labelCol='label', metricName='ndcgAt', k=3)[source]¶

Bases: pyspark.ml.evaluation.JavaEvaluator, pyspark.ml.param.shared.HasLabelCol, pyspark.ml.param.shared.HasPredictionCol, pyspark.ml.util.JavaMLReadable, pyspark.ml.util.JavaMLWritable

getK()[source]¶: Gets the value of metricName or its default value.

getMetricName()[source]¶: Gets the value of metricName or its default value.

getMetricsMap(dataframe)[source]¶

getRawPredictionCol()[source]¶: Gets the value of rawPredictionCol or its default value.

k = Param(parent='undefined', name='k', doc='k')¶

labelCol = Param(parent='undefined', name='labelCol', doc='labelCol')¶

metricName = Param(parent='undefined', name='metricName', doc='metric name in evaluation - one of:\n map - \n ndcgAt - \n mapk - \n recallAtK - \n diversityAtK - \n maxDiversity - ')¶

nItems = Param(parent='undefined', name='nItems', doc='number of items')¶

rawPredictionCol = Param(parent='undefined', name='rawPredictionCol', doc='rawPredictionCol')¶

setK(value)[source]¶: Sets the value of metricName.

setMetricName(value)[source]¶: Sets the value of metricName.

setNumberItems(value)[source]¶: Sets the value of nItems.

setParams(self, rawPredictionCol="rawPrediction", labelCol="label", metricName="ndcgAt")[source]¶: Sets params for binary classification evaluator.

setRawPredictionCol(value)[source]¶: Sets the value of rawPredictionCol.