Package org.apache.spark.ml.evaluation
Class MultilabelClassificationEvaluator
Object
org.apache.spark.ml.evaluation.Evaluator
org.apache.spark.ml.evaluation.MultilabelClassificationEvaluator
- All Implemented Interfaces:
Serializable,Params,HasLabelCol,HasPredictionCol,DefaultParamsWritable,Identifiable,MLWritable
public class MultilabelClassificationEvaluator
extends Evaluator
implements HasPredictionCol, HasLabelCol, DefaultParamsWritable
:: Experimental ::
Evaluator for multi-label classification, which expects two input
columns: prediction and label.
- See Also:
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Constructor Summary
ConstructorsConstructorDescription -
Method Summary
Modifier and TypeMethodDescriptionCreates a copy of this instance with the same UID and some extra params.doubleEvaluates model output and returns a scalar metric.doublegetMetrics(Dataset<?> dataset) Get a MultilabelMetrics, which can be used to get multilabel classification metrics such as accuracy, precision, precisionByLabel, etc.booleanIndicates whether the metric returned byevaluateshould be maximized (true, default) or minimized (false).labelCol()Param for label column name.final DoubleParamparam for the class whose metric will be computed in"precisionByLabel","recallByLabel","f1MeasureByLabel".param for metric name in evaluation (supports"f1Measure"(default),"subsetAccuracy","accuracy","hammingLoss","precision","recall","precisionByLabel","recallByLabel","f1MeasureByLabel","microPrecision","microRecall","microF1Measure")Param for prediction column name.static MLReader<T>read()setLabelCol(String value) setMetricLabel(double value) setMetricName(String value) setPredictionCol(String value) toString()uid()An immutable unique ID for the object and its derivatives.Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, waitMethods inherited from interface org.apache.spark.ml.util.DefaultParamsWritable
writeMethods inherited from interface org.apache.spark.ml.param.shared.HasLabelCol
getLabelColMethods inherited from interface org.apache.spark.ml.param.shared.HasPredictionCol
getPredictionColMethods inherited from interface org.apache.spark.ml.util.MLWritable
saveMethods 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
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Constructor Details
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MultilabelClassificationEvaluator
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MultilabelClassificationEvaluator
public MultilabelClassificationEvaluator()
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Method Details
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load
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read
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labelCol
Description copied from interface:HasLabelColParam for label column name.- Specified by:
labelColin interfaceHasLabelCol- Returns:
- (undocumented)
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predictionCol
Description copied from interface:HasPredictionColParam for prediction column name.- Specified by:
predictionColin interfaceHasPredictionCol- Returns:
- (undocumented)
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uid
Description copied from interface:IdentifiableAn immutable unique ID for the object and its derivatives.- Specified by:
uidin interfaceIdentifiable- Returns:
- (undocumented)
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metricName
param for metric name in evaluation (supports"f1Measure"(default),"subsetAccuracy","accuracy","hammingLoss","precision","recall","precisionByLabel","recallByLabel","f1MeasureByLabel","microPrecision","microRecall","microF1Measure")- Returns:
- (undocumented)
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getMetricName
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setMetricName
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metricLabel
param for the class whose metric will be computed in"precisionByLabel","recallByLabel","f1MeasureByLabel".- Returns:
- (undocumented)
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getMetricLabel
public double getMetricLabel() -
setMetricLabel
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setPredictionCol
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setLabelCol
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evaluate
Description copied from class:EvaluatorEvaluates model output and returns a scalar metric. The value ofEvaluator.isLargerBetter()specifies whether larger values are better. -
getMetrics
Get a MultilabelMetrics, which can be used to get multilabel classification metrics such as accuracy, precision, precisionByLabel, etc.- Parameters:
dataset- a dataset that contains labels/observations and predictions.- Returns:
- MultilabelMetrics
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isLargerBetter
public boolean isLargerBetter()Description copied from class:EvaluatorIndicates whether the metric returned byevaluateshould be maximized (true, default) or minimized (false). A given evaluator may support multiple metrics which may be maximized or minimized.- Overrides:
isLargerBetterin classEvaluator- Returns:
- (undocumented)
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copy
Description copied from interface:ParamsCreates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. SeedefaultCopy(). -
toString
- Specified by:
toStringin interfaceIdentifiable- Overrides:
toStringin classObject
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