com.google.api.services.bigquery.model

Class RegressionMetrics

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.RegressionMetrics

All Implemented Interfaces:

Cloneable, Map<String,Object>

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

Evaluation metrics for regression and explicit feedback type matrix factorization 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
RegressionMetrics()

Method Summary

Modifier and Type	Method and Description
RegressionMetrics	clone()
Double	getMeanAbsoluteError() Mean absolute error.
Double	getMeanSquaredError() Mean squared error.
Double	getMeanSquaredLogError() Mean squared log error.
Double	getMedianAbsoluteError() Median absolute error.
Double	getRSquared() R^2 score.
RegressionMetrics	set(String fieldName, Object value)
RegressionMetrics	setMeanAbsoluteError(Double meanAbsoluteError) Mean absolute error.
RegressionMetrics	setMeanSquaredError(Double meanSquaredError) Mean squared error.
RegressionMetrics	setMeanSquaredLogError(Double meanSquaredLogError) Mean squared log error.
RegressionMetrics	setMedianAbsoluteError(Double medianAbsoluteError) Median absolute error.
RegressionMetrics	setRSquared(Double rSquared) R^2 score.

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

RegressionMetrics

public RegressionMetrics()

Method Detail

getMeanAbsoluteError

public Double getMeanAbsoluteError()

Mean absolute error.

Returns:

value or null for none

setMeanAbsoluteError

public RegressionMetrics setMeanAbsoluteError(Double meanAbsoluteError)

Mean absolute error.

Parameters:

meanAbsoluteError - meanAbsoluteError or null for none

getMeanSquaredError

public Double getMeanSquaredError()

Mean squared error.

Returns:

value or null for none

setMeanSquaredError

public RegressionMetrics setMeanSquaredError(Double meanSquaredError)

Mean squared error.

Parameters:

meanSquaredError - meanSquaredError or null for none

getMeanSquaredLogError

public Double getMeanSquaredLogError()

Mean squared log error.

Returns:

value or null for none

setMeanSquaredLogError

public RegressionMetrics setMeanSquaredLogError(Double meanSquaredLogError)

Mean squared log error.

Parameters:

meanSquaredLogError - meanSquaredLogError or null for none

getMedianAbsoluteError

public Double getMedianAbsoluteError()

Median absolute error.

Returns:

value or null for none

setMedianAbsoluteError

public RegressionMetrics setMedianAbsoluteError(Double medianAbsoluteError)

Median absolute error.

Parameters:

medianAbsoluteError - medianAbsoluteError or null for none

getRSquared

public Double getRSquared()

R^2 score. This corresponds to r2_score in ML.EVALUATE.

Returns:

value or null for none

setRSquared

public RegressionMetrics setRSquared(Double rSquared)

R^2 score. This corresponds to r2_score in ML.EVALUATE.

Parameters:

rSquared - rSquared or null for none

set

public RegressionMetrics set(String fieldName,
                             Object value)

Overrides:

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

clone

public RegressionMetrics clone()

Overrides:

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