com.google.api.services.bigquery.model

Class EvaluationMetrics

java.lang.Object

java.util.AbstractMap<String,Object>

com.google.api.client.util.GenericData

com.google.api.client.json.GenericJson

com.google.api.services.bigquery.model.EvaluationMetrics

All Implemented Interfaces:

Cloneable, Map<String,Object>

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

Evaluation metrics of a model. These are either computed on all training data or just the eval data based on whether eval data was used during training. These are not present for imported models.

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 BigQuery 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
EvaluationMetrics()

Method Summary

Modifier and Type	Method and Description
EvaluationMetrics	clone()
ArimaForecastingMetrics	getArimaForecastingMetrics() Populated for ARIMA models.
BinaryClassificationMetrics	getBinaryClassificationMetrics() Populated for binary classification/classifier models.
ClusteringMetrics	getClusteringMetrics() Populated for clustering models.
DimensionalityReductionMetrics	getDimensionalityReductionMetrics() Evaluation metrics when the model is a dimensionality reduction model, which currently includes PCA.
MultiClassClassificationMetrics	getMultiClassClassificationMetrics() Populated for multi-class classification/classifier models.
RankingMetrics	getRankingMetrics() Populated for implicit feedback type matrix factorization models.
RegressionMetrics	getRegressionMetrics() Populated for regression models and explicit feedback type matrix factorization models.
EvaluationMetrics	set(String fieldName, Object value)
EvaluationMetrics	setArimaForecastingMetrics(ArimaForecastingMetrics arimaForecastingMetrics) Populated for ARIMA models.
EvaluationMetrics	setBinaryClassificationMetrics(BinaryClassificationMetrics binaryClassificationMetrics) Populated for binary classification/classifier models.
EvaluationMetrics	setClusteringMetrics(ClusteringMetrics clusteringMetrics) Populated for clustering models.
EvaluationMetrics	setDimensionalityReductionMetrics(DimensionalityReductionMetrics dimensionalityReductionMetrics) Evaluation metrics when the model is a dimensionality reduction model, which currently includes PCA.
EvaluationMetrics	setMultiClassClassificationMetrics(MultiClassClassificationMetrics multiClassClassificationMetrics) Populated for multi-class classification/classifier models.
EvaluationMetrics	setRankingMetrics(RankingMetrics rankingMetrics) Populated for implicit feedback type matrix factorization models.
EvaluationMetrics	setRegressionMetrics(RegressionMetrics regressionMetrics) Populated for regression models and explicit feedback type matrix factorization models.

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

EvaluationMetrics

public EvaluationMetrics()

Method Detail

getArimaForecastingMetrics

public ArimaForecastingMetrics getArimaForecastingMetrics()

Populated for ARIMA models.

Returns:

value or null for none

setArimaForecastingMetrics

public EvaluationMetrics setArimaForecastingMetrics(ArimaForecastingMetrics arimaForecastingMetrics)

Populated for ARIMA models.

Parameters:

arimaForecastingMetrics - arimaForecastingMetrics or null for none

getBinaryClassificationMetrics

public BinaryClassificationMetrics getBinaryClassificationMetrics()

Populated for binary classification/classifier models.

Returns:

value or null for none

setBinaryClassificationMetrics

public EvaluationMetrics setBinaryClassificationMetrics(BinaryClassificationMetrics binaryClassificationMetrics)

Populated for binary classification/classifier models.

Parameters:

binaryClassificationMetrics - binaryClassificationMetrics or null for none

getClusteringMetrics

public ClusteringMetrics getClusteringMetrics()

Populated for clustering models.

Returns:

value or null for none

setClusteringMetrics

public EvaluationMetrics setClusteringMetrics(ClusteringMetrics clusteringMetrics)

Populated for clustering models.

Parameters:

clusteringMetrics - clusteringMetrics or null for none

getDimensionalityReductionMetrics

public DimensionalityReductionMetrics getDimensionalityReductionMetrics()

Evaluation metrics when the model is a dimensionality reduction model, which currently includes PCA.

Returns:

value or null for none

setDimensionalityReductionMetrics

public EvaluationMetrics setDimensionalityReductionMetrics(DimensionalityReductionMetrics dimensionalityReductionMetrics)

Evaluation metrics when the model is a dimensionality reduction model, which currently includes PCA.

Parameters:

dimensionalityReductionMetrics - dimensionalityReductionMetrics or null for none

getMultiClassClassificationMetrics

public MultiClassClassificationMetrics getMultiClassClassificationMetrics()

Populated for multi-class classification/classifier models.

Returns:

value or null for none

setMultiClassClassificationMetrics

public EvaluationMetrics setMultiClassClassificationMetrics(MultiClassClassificationMetrics multiClassClassificationMetrics)

Populated for multi-class classification/classifier models.

Parameters:

multiClassClassificationMetrics - multiClassClassificationMetrics or null for none

getRankingMetrics

public RankingMetrics getRankingMetrics()

Populated for implicit feedback type matrix factorization models.

Returns:

value or null for none

setRankingMetrics

public EvaluationMetrics setRankingMetrics(RankingMetrics rankingMetrics)

Populated for implicit feedback type matrix factorization models.

Parameters:

rankingMetrics - rankingMetrics or null for none

getRegressionMetrics

public RegressionMetrics getRegressionMetrics()

Populated for regression models and explicit feedback type matrix factorization models.

Returns:

value or null for none

setRegressionMetrics

public EvaluationMetrics setRegressionMetrics(RegressionMetrics regressionMetrics)

Populated for regression models and explicit feedback type matrix factorization models.

Parameters:

regressionMetrics - regressionMetrics or null for none

set

public EvaluationMetrics set(String fieldName,
                             Object value)

Overrides:

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

clone

public EvaluationMetrics clone()

Overrides:

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