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

public final class RegressionEvaluator
extends Evaluator

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

See Also:

Serialized Form

Constructor Summary

RegressionEvaluator()

RegressionEvaluator(String uid)

Method Summary

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.
String	getMetricName()
Param<String>	metricName() param for metric name in evaluation (supports "rmse" (default), "mse", "r2", and "mae")
RegressionEvaluator	setLabelCol(String value)
RegressionEvaluator	setMetricName(String value)
RegressionEvaluator	setPredictionCol(String value)
String	uid()

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.Params

clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, setDefault, shouldOwn, validateParams

Constructor Detail

RegressionEvaluator

public RegressionEvaluator(String uid)

RegressionEvaluator

public RegressionEvaluator()

Method Detail

uid

public String uid()

metricName

public Param<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 String getMetricName()

setMetricName

public RegressionEvaluator setMetricName(String value)

setPredictionCol

public RegressionEvaluator setPredictionCol(String value)

setLabelCol

public RegressionEvaluator setLabelCol(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

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()