Package org.apache.spark.ml.evaluation

Class RankingEvaluator

Object

org.apache.spark.ml.evaluation.Evaluator

org.apache.spark.ml.evaluation.RankingEvaluator

All Implemented Interfaces:

Serializable, Params, HasLabelCol, HasPredictionCol, DefaultParamsWritable, Identifiable, MLWritable

public class RankingEvaluator
extends Evaluator
implements HasPredictionCol, HasLabelCol, DefaultParamsWritable

:: Experimental :: Evaluator for ranking, which expects two input columns: prediction and label.

See Also:

• Serialized Form

Constructor Summary

Constructors

Constructor	Description
RankingEvaluator()
RankingEvaluator(String uid)

Method Summary

Modifier and Type	Method	Description
RankingEvaluator	copy(ParamMap extra)	Creates a copy of this instance with the same UID and some extra params.
double	evaluate(Dataset<?> dataset)	Evaluates model output and returns a scalar metric.
int	getK()
String	getMetricName()
RankingMetrics<Object>	getMetrics(Dataset<?> dataset)	Get a RankingMetrics, which can be used to get ranking metrics such as meanAveragePrecision, meanAveragePrecisionAtK, etc.
boolean	isLargerBetter()	Indicates whether the metric returned by evaluate should be maximized (true, default) or minimized (false).
final IntParam	k()	param for ranking position value used in "meanAveragePrecisionAtK", "precisionAtK", "ndcgAtK", "recallAtK".
final Param<String>	labelCol()	Param for label column name.
static RankingEvaluator	load(String path)
final Param<String>	metricName()	param for metric name in evaluation (supports "meanAveragePrecision" (default), "meanAveragePrecisionAtK", "precisionAtK", "ndcgAtK", "recallAtK")
final Param<String>	predictionCol()	Param for prediction column name.
static MLReader<T>	read()
RankingEvaluator	setK(int value)
RankingEvaluator	setLabelCol(String value)
RankingEvaluator	setMetricName(String value)
RankingEvaluator	setPredictionCol(String value)
String	toString()
String	uid()	An immutable unique ID for the object and its derivatives.

Methods inherited from class org.apache.spark.ml.evaluation.Evaluator

evaluate, params

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface org.apache.spark.ml.util.DefaultParamsWritable

write

Methods inherited from interface org.apache.spark.ml.param.shared.HasLabelCol

getLabelCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasPredictionCol

getPredictionCol

Methods inherited from interface org.apache.spark.ml.util.MLWritable

save

Methods inherited from interface org.apache.spark.ml.param.Params

clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

Constructor Details

RankingEvaluator

public RankingEvaluator(String uid)

RankingEvaluator

public RankingEvaluator()

Method Details

load

public static RankingEvaluator load(String path)

read

public static MLReader<T> read()

labelCol

public final Param<String> labelCol()

Description copied from interface: HasLabelCol

Param for label column name.

Specified by:

labelCol in interface HasLabelCol

Returns:

(undocumented)

predictionCol

public final Param<String> predictionCol()

Description copied from interface: HasPredictionCol

Param for prediction column name.

Specified by:

predictionCol in interface HasPredictionCol

Returns:

(undocumented)

uid

public String uid()

Description copied from interface: Identifiable

An immutable unique ID for the object and its derivatives.

Specified by:

uid in interface Identifiable

Returns:

(undocumented)

metricName

public final Param<String> metricName()

param for metric name in evaluation (supports "meanAveragePrecision" (default), "meanAveragePrecisionAtK", "precisionAtK", "ndcgAtK", "recallAtK")

Returns:

(undocumented)

getMetricName

public String getMetricName()

setMetricName

public RankingEvaluator setMetricName(String value)

k

public final IntParam k()

param for ranking position value used in "meanAveragePrecisionAtK", "precisionAtK", "ndcgAtK", "recallAtK". Must be > 0. The default value is 10.

Returns:

(undocumented)

getK

public int getK()

setK

public RankingEvaluator setK(int value)

setPredictionCol

public RankingEvaluator setPredictionCol(String value)

setLabelCol

public RankingEvaluator setLabelCol(String value)

evaluate

public double evaluate(Dataset<?> dataset)

Description copied from class: Evaluator

Evaluates model output and returns a scalar metric. The value of Evaluator.isLargerBetter() specifies whether larger values are better.

Specified by:

evaluate in class Evaluator

Parameters:

dataset - a dataset that contains labels/observations and predictions.

Returns:

metric

getMetrics

public RankingMetrics<Object> getMetrics(Dataset<?> dataset)

Get a RankingMetrics, which can be used to get ranking metrics such as meanAveragePrecision, meanAveragePrecisionAtK, etc.

Parameters:

dataset - a dataset that contains labels/observations and predictions.

Returns:

RankingMetrics

isLargerBetter

public boolean isLargerBetter()

Description copied from class: Evaluator

Indicates whether the metric returned by evaluate should be maximized (true, default) or minimized (false). A given evaluator may support multiple metrics which may be maximized or minimized.

Overrides:

isLargerBetter in class Evaluator

Returns:

(undocumented)

copy

public RankingEvaluator copy(ParamMap extra)

Description copied from interface: Params

Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. See defaultCopy().

Specified by:

copy in interface Params

Specified by:

copy in class Evaluator

Parameters:

extra - (undocumented)

Returns:

(undocumented)

toString

public String toString()

Specified by:

toString in interface Identifiable

Overrides:

toString in class Object