org.apache.spark.ml.evaluation

Class RegressionEvaluator

Object

org.apache.spark.ml.evaluation.Evaluator

org.apache.spark.ml.evaluation.RegressionEvaluator

All Implemented Interfaces:

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

public final class RegressionEvaluator
extends Evaluator
implements HasPredictionCol, HasLabelCol, DefaultParamsWritable

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

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
RegressionEvaluator()
RegressionEvaluator(String uid)

Method Summary

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(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 RegressionEvaluator	load(String path)
Param<String>	metricName() Param for metric name in evaluation.
static MLReader<T>	read()
RegressionEvaluator	setLabelCol(String value)
RegressionEvaluator	setMetricName(String value)
RegressionEvaluator	setPredictionCol(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.HasPredictionCol

getPredictionCol, predictionCol

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

RegressionEvaluator

public RegressionEvaluator(String uid)

RegressionEvaluator

public RegressionEvaluator()

Method Detail

load

public static RegressionEvaluator 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: - "rmse" (default): root mean squared error - "mse": mean squared error - "r2": R^2^ metric - "mae": mean absolute error

Returns:

(undocumented)

getMetricName

public String getMetricName()

setMetricName

public RegressionEvaluator setMetricName(String value)

setPredictionCol

public RegressionEvaluator setPredictionCol(String value)

setLabelCol

public RegressionEvaluator 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 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. See defaultCopy().

Specified by:

copy in interface Params

Specified by:

copy in class Evaluator

Parameters:

extra - (undocumented)

Returns:

(undocumented)