org.apache.spark.ml.evaluation

Class BinaryClassificationEvaluator

Object

org.apache.spark.ml.evaluation.Evaluator

org.apache.spark.ml.evaluation.BinaryClassificationEvaluator

All Implemented Interfaces:

java.io.Serializable, Params, HasLabelCol, HasRawPredictionCol, DefaultParamsWritable, Identifiable, MLWritable

public class BinaryClassificationEvaluator
extends Evaluator
implements HasRawPredictionCol, HasLabelCol, DefaultParamsWritable

:: 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).

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
BinaryClassificationEvaluator()
BinaryClassificationEvaluator(String uid)

Method Summary

Modifier and Type	Method and Description
BinaryClassificationEvaluator	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.
String	getMetricName()
boolean	isLargerBetter() Indicates whether the metric returned by evaluate should be maximized (true, default) or minimized (false).
static BinaryClassificationEvaluator	load(String path)
Param<String>	metricName() param for metric name in evaluation (supports "areaUnderROC" (default), "areaUnderPR")
static MLReader<T>	read()
BinaryClassificationEvaluator	setLabelCol(String value)
BinaryClassificationEvaluator	setMetricName(String value)
BinaryClassificationEvaluator	setRawPredictionCol(String value)
String	uid() An immutable unique ID for the object and its derivatives.

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

evaluate

Methods inherited from class Object

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

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

getRawPredictionCol, rawPredictionCol

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

getLabelCol, labelCol

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, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

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

toString

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

write

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

save

Constructor Detail

BinaryClassificationEvaluator

public BinaryClassificationEvaluator(String uid)

BinaryClassificationEvaluator

public BinaryClassificationEvaluator()

Method Detail

load

public static BinaryClassificationEvaluator load(String path)

read

public static MLReader<T> read()

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 Param<String> metricName()

param for metric name in evaluation (supports "areaUnderROC" (default), "areaUnderPR")

Returns:

(undocumented)

getMetricName

public String getMetricName()

setMetricName

public BinaryClassificationEvaluator setMetricName(String value)

setRawPredictionCol

public BinaryClassificationEvaluator setRawPredictionCol(String value)

setLabelCol

public BinaryClassificationEvaluator 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 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

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 BinaryClassificationEvaluator 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)