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
,scala.Serializable
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
ConstructorDescription -
Method Summary
Modifier and TypeMethodDescriptionCreates a copy of this instance with the same UID and some extra params.double
Evaluates model output and returns a scalar metric.double
getMetrics
(Dataset<?> dataset) Get a MultilabelMetrics, which can be used to get multilabel classification metrics such as accuracy, precision, precisionByLabel, etc.boolean
Indicates whether the metric returned byevaluate
should be maximized (true, default) or minimized (false).labelCol()
Param for label column name.final DoubleParam
param 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, 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
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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:HasLabelCol
Param for label column name.- Specified by:
labelCol
in interfaceHasLabelCol
- Returns:
- (undocumented)
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predictionCol
Description copied from interface:HasPredictionCol
Param for prediction column name.- Specified by:
predictionCol
in interfaceHasPredictionCol
- Returns:
- (undocumented)
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uid
Description copied from interface:Identifiable
An immutable unique ID for the object and its derivatives.- Specified by:
uid
in 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:Evaluator
Evaluates 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:Evaluator
Indicates whether the metric returned byevaluate
should be maximized (true, default) or minimized (false). A given evaluator may support multiple metrics which may be maximized or minimized.- Overrides:
isLargerBetter
in classEvaluator
- Returns:
- (undocumented)
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copy
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. SeedefaultCopy()
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toString
- Specified by:
toString
in interfaceIdentifiable
- Overrides:
toString
in classObject
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