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

Constructors

Constructor and Description
RegressionEvaluator()
RegressionEvaluator(String uid)

Method Summary

Methods

Modifier and Type	Method and Description
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

copy, 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, 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")

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