com.google.api.services.language.v2.model

Class XPSRegressionEvaluationMetrics

java.lang.Object

java.util.AbstractMap<String,Object>

com.google.api.client.util.GenericData

com.google.api.client.json.GenericJson

com.google.api.services.language.v2.model.XPSRegressionEvaluationMetrics

All Implemented Interfaces:

Cloneable, Map<String,Object>

public final class XPSRegressionEvaluationMetrics
extends com.google.api.client.json.GenericJson

Model evaluation metrics for regression problems. It can be used for Tables.

This is the Java data model class that specifies how to parse/serialize into the JSON that is transmitted over HTTP when working with the Cloud Natural Language API. For a detailed explanation see: https://developers.google.com/api-client-library/java/google-http-java-client/json

Author:

Google, Inc.

Nested Class Summary

Nested classes/interfaces inherited from class com.google.api.client.util.GenericData

com.google.api.client.util.GenericData.Flags

Nested classes/interfaces inherited from class java.util.AbstractMap

AbstractMap.SimpleEntry<K,V>, AbstractMap.SimpleImmutableEntry<K,V>

Nested classes/interfaces inherited from interface java.util.Map

Map.Entry<K,V>

Constructor Summary

Constructors

Constructor and Description
XPSRegressionEvaluationMetrics()

Method Summary

Modifier and Type	Method and Description
XPSRegressionEvaluationMetrics	clone()
Float	getMeanAbsoluteError() Mean Absolute Error (MAE).
Float	getMeanAbsolutePercentageError() Mean absolute percentage error.
List<XPSRegressionMetricsEntry>	getRegressionMetricsEntries() A list of actual versus predicted points for the model being evaluated.
Float	getRootMeanSquaredError() Root Mean Squared Error (RMSE).
Float	getRootMeanSquaredLogError() Root mean squared log error.
Float	getRSquared() R squared.
XPSRegressionEvaluationMetrics	set(String fieldName, Object value)
XPSRegressionEvaluationMetrics	setMeanAbsoluteError(Float meanAbsoluteError) Mean Absolute Error (MAE).
XPSRegressionEvaluationMetrics	setMeanAbsolutePercentageError(Float meanAbsolutePercentageError) Mean absolute percentage error.
XPSRegressionEvaluationMetrics	setRegressionMetricsEntries(List<XPSRegressionMetricsEntry> regressionMetricsEntries) A list of actual versus predicted points for the model being evaluated.
XPSRegressionEvaluationMetrics	setRootMeanSquaredError(Float rootMeanSquaredError) Root Mean Squared Error (RMSE).
XPSRegressionEvaluationMetrics	setRootMeanSquaredLogError(Float rootMeanSquaredLogError) Root mean squared log error.
XPSRegressionEvaluationMetrics	setRSquared(Float rSquared) R squared.

Methods inherited from class com.google.api.client.json.GenericJson

getFactory, setFactory, toPrettyString, toString

Methods inherited from class com.google.api.client.util.GenericData

entrySet, equals, get, getClassInfo, getUnknownKeys, hashCode, put, putAll, remove, setUnknownKeys

Methods inherited from class java.util.AbstractMap

clear, containsKey, containsValue, isEmpty, keySet, size, values

Methods inherited from class java.lang.Object

finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface java.util.Map

compute, computeIfAbsent, computeIfPresent, forEach, getOrDefault, merge, putIfAbsent, remove, replace, replace, replaceAll

Constructor Detail

XPSRegressionEvaluationMetrics

public XPSRegressionEvaluationMetrics()

Method Detail

getMeanAbsoluteError

public Float getMeanAbsoluteError()

Mean Absolute Error (MAE).

Returns:

value or null for none

setMeanAbsoluteError

public XPSRegressionEvaluationMetrics setMeanAbsoluteError(Float meanAbsoluteError)

Mean Absolute Error (MAE).

Parameters:

meanAbsoluteError - meanAbsoluteError or null for none

getMeanAbsolutePercentageError

public Float getMeanAbsolutePercentageError()

Mean absolute percentage error. Only set if all ground truth values are positive.

Returns:

value or null for none

setMeanAbsolutePercentageError

public XPSRegressionEvaluationMetrics setMeanAbsolutePercentageError(Float meanAbsolutePercentageError)

Mean absolute percentage error. Only set if all ground truth values are positive.

Parameters:

meanAbsolutePercentageError - meanAbsolutePercentageError or null for none

getRSquared

public Float getRSquared()

R squared.

Returns:

value or null for none

setRSquared

public XPSRegressionEvaluationMetrics setRSquared(Float rSquared)

R squared.

Parameters:

rSquared - rSquared or null for none

getRegressionMetricsEntries

public List<XPSRegressionMetricsEntry> getRegressionMetricsEntries()

A list of actual versus predicted points for the model being evaluated.

Returns:

value or null for none

setRegressionMetricsEntries

public XPSRegressionEvaluationMetrics setRegressionMetricsEntries(List<XPSRegressionMetricsEntry> regressionMetricsEntries)

A list of actual versus predicted points for the model being evaluated.

Parameters:

regressionMetricsEntries - regressionMetricsEntries or null for none

getRootMeanSquaredError

public Float getRootMeanSquaredError()

Root Mean Squared Error (RMSE).

Returns:

value or null for none

setRootMeanSquaredError

public XPSRegressionEvaluationMetrics setRootMeanSquaredError(Float rootMeanSquaredError)

Root Mean Squared Error (RMSE).

Parameters:

rootMeanSquaredError - rootMeanSquaredError or null for none

getRootMeanSquaredLogError

public Float getRootMeanSquaredLogError()

Root mean squared log error.

Returns:

value or null for none

setRootMeanSquaredLogError

public XPSRegressionEvaluationMetrics setRootMeanSquaredLogError(Float rootMeanSquaredLogError)

Root mean squared log error.

Parameters:

rootMeanSquaredLogError - rootMeanSquaredLogError or null for none

set

public XPSRegressionEvaluationMetrics set(String fieldName,
                                          Object value)

Overrides:

set in class com.google.api.client.json.GenericJson

clone

public XPSRegressionEvaluationMetrics clone()

Overrides:

clone in class com.google.api.client.json.GenericJson