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, DefaultParamsWritable, Identifiable, MLWritable

public final class RegressionEvaluator
extends Evaluator
implements 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

Methods

Modifier and Type	Method and Description
static Params	clear(Param<?> param)
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.
static String	explainParam(Param<?> param)
static String	explainParams()
static ParamMap	extractParamMap()
static ParamMap	extractParamMap(ParamMap extra)
static <T> scala.Option<T>	get(Param<T> param)
static <T> scala.Option<T>	getDefault(Param<T> param)
static String	getLabelCol()
String	getMetricName()
static <T> T	getOrDefault(Param<T> param)
static Param<Object>	getParam(String paramName)
static String	getPredictionCol()
static <T> boolean	hasDefault(Param<T> param)
static boolean	hasParam(String paramName)
static boolean	isDefined(Param<?> param)
boolean	isLargerBetter() Indicates whether the metric returned by evaluate should be maximized (true, default) or minimized (false).
static boolean	isSet(Param<?> param)
static Param<String>	labelCol()
static RegressionEvaluator	load(String path)
Param<String>	metricName() Param for metric name in evaluation.
static Param<?>[]	params()
static Param<String>	predictionCol()
static void	save(String path)
static <T> Params	set(Param<T> param, T value)
RegressionEvaluator	setLabelCol(String value)
RegressionEvaluator	setMetricName(String value)
RegressionEvaluator	setPredictionCol(String value)
static String	toString()
String	uid() An immutable unique ID for the object and its derivatives.
static MLWriter	write()

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.util.DefaultParamsWritable

write

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

save

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

Constructor Detail

RegressionEvaluator

public RegressionEvaluator(String uid)

RegressionEvaluator

public RegressionEvaluator()

Method Detail

load

public static RegressionEvaluator load(String path)

toString

public static String toString()

params

public static Param<?>[] params()

explainParam

public static String explainParam(Param<?> param)

explainParams

public static String explainParams()

isSet

public static final boolean isSet(Param<?> param)

isDefined

public static final boolean isDefined(Param<?> param)

hasParam

public static boolean hasParam(String paramName)

getParam

public static Param<Object> getParam(String paramName)

set

public static final <T> Params set(Param<T> param,
             T value)

get

public static final <T> scala.Option<T> get(Param<T> param)

clear

public static final Params clear(Param<?> param)

getOrDefault

public static final <T> T getOrDefault(Param<T> param)

getDefault

public static final <T> scala.Option<T> getDefault(Param<T> param)

hasDefault

public static final <T> boolean hasDefault(Param<T> param)

extractParamMap

public static final ParamMap extractParamMap(ParamMap extra)

extractParamMap

public static final ParamMap extractParamMap()

predictionCol

public static final Param<String> predictionCol()

getPredictionCol

public static final String getPredictionCol()

labelCol

public static final Param<String> labelCol()

getLabelCol

public static final String getLabelCol()

save

public static void save(String path)
                 throws java.io.IOException

Throws:

java.io.IOException

write

public static MLWriter write()

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)