org.apache.spark.ml.evaluation

Class RegressionEvaluator

java.lang.Object

org.apache.spark.ml.evaluation.Evaluator

org.apache.spark.ml.evaluation.RegressionEvaluator

All Implemented Interfaces:

java.io.Serializable, Params, Identifiable

public final class RegressionEvaluator
extends Evaluator

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

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
RegressionEvaluator()
RegressionEvaluator(java.lang.String uid)

Method Summary

Methods

Modifier and Type	Method and Description
RegressionEvaluator	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
double	evaluate(DataFrame dataset) Evaluates the output.
java.lang.String	getMetricName()
boolean	isLargerBetter() Indicates whether the metric returned by evaluate() should be maximized (true, default) or minimized (false).
Param<java.lang.String>	metricName() param for metric name in evaluation (supports "rmse" (default), "mse", "r2", and "mae")
RegressionEvaluator	setLabelCol(java.lang.String value)
RegressionEvaluator	setMetricName(java.lang.String value)
RegressionEvaluator	setPredictionCol(java.lang.String value)
java.lang.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 java.lang.Object

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

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, validateParams

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

toString

Constructor Detail

RegressionEvaluator

public RegressionEvaluator(java.lang.String uid)

RegressionEvaluator

public RegressionEvaluator()

Method Detail

uid

public java.lang.String uid()

Description copied from interface: Identifiable

An immutable unique ID for the object and its derivatives.

Returns:

(undocumented)

metricName

public Param<java.lang.String> metricName()

param for metric name in evaluation (supports "rmse" (default), "mse", "r2", and "mae")

Because we will maximize evaluation value (ref: CrossValidator), when we evaluate a metric that is needed to minimize (e.g., "rmse", "mse", "mae"), we take and output the negative of this metric.

Returns:

(undocumented)

getMetricName

public java.lang.String getMetricName()

setMetricName

public RegressionEvaluator setMetricName(java.lang.String value)

setPredictionCol

public RegressionEvaluator setPredictionCol(java.lang.String value)

setLabelCol

public RegressionEvaluator setLabelCol(java.lang.String value)

evaluate

public double evaluate(DataFrame dataset)

Description copied from class: Evaluator

Evaluates the output.

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 RegressionEvaluator 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.

Specified by:

copy in interface Params

Specified by:

copy in class Evaluator

Parameters:

extra - (undocumented)

Returns:

(undocumented)

See Also:

defaultCopy()