package evaluation
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Type Members
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class
BinaryClassificationEvaluator extends Evaluator with HasRawPredictionCol with HasLabelCol with DefaultParamsWritable
:: Experimental :: Evaluator for binary classification, which expects two input columns: rawPrediction and label.
:: Experimental :: Evaluator for binary classification, which expects two input columns: rawPrediction and label. The rawPrediction column can be of type double (binary 0/1 prediction, or probability of label 1) or of type vector (length-2 vector of raw predictions, scores, or label probabilities).
- Annotations
- @Since( "1.2.0" ) @Experimental()
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class
ClusteringEvaluator extends Evaluator with HasPredictionCol with HasFeaturesCol with DefaultParamsWritable
:: Experimental ::
:: Experimental ::
Evaluator for clustering results. The metric computes the Silhouette measure using the specified distance measure.
The Silhouette is a measure for the validation of the consistency within clusters. It ranges between 1 and -1, where a value close to 1 means that the points in a cluster are close to the other points in the same cluster and far from the points of the other clusters.
- Annotations
- @Experimental() @Since( "2.3.0" )
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abstract
class
Evaluator extends Params
:: DeveloperApi :: Abstract class for evaluators that compute metrics from predictions.
:: DeveloperApi :: Abstract class for evaluators that compute metrics from predictions.
- Annotations
- @Since( "1.5.0" ) @DeveloperApi()
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class
MulticlassClassificationEvaluator extends Evaluator with HasPredictionCol with HasLabelCol with HasWeightCol with DefaultParamsWritable
:: Experimental :: Evaluator for multiclass classification, which expects two input columns: prediction and label.
:: Experimental :: Evaluator for multiclass classification, which expects two input columns: prediction and label.
- Annotations
- @Since( "1.5.0" ) @Experimental()
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final
class
RegressionEvaluator extends Evaluator with HasPredictionCol with HasLabelCol with DefaultParamsWritable
:: Experimental :: Evaluator for regression, which expects two input columns: prediction and label.
:: Experimental :: Evaluator for regression, which expects two input columns: prediction and label.
- Annotations
- @Since( "1.4.0" ) @Experimental()
Value Members
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object
BinaryClassificationEvaluator extends DefaultParamsReadable[BinaryClassificationEvaluator] with Serializable
- Annotations
- @Since( "1.6.0" )
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object
ClusteringEvaluator extends DefaultParamsReadable[ClusteringEvaluator] with Serializable
- Annotations
- @Since( "2.3.0" )
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object
MulticlassClassificationEvaluator extends DefaultParamsReadable[MulticlassClassificationEvaluator] with Serializable
- Annotations
- @Since( "1.6.0" )
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object
RegressionEvaluator extends DefaultParamsReadable[RegressionEvaluator] with Serializable
- Annotations
- @Since( "1.6.0" )