com.google.api.services.bigquery.model

Class BqmlIterationResult

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.BqmlIterationResult

All Implemented Interfaces:

Cloneable, Map<String,Object>

public final class BqmlIterationResult
extends GenericJson

Model definition for BqmlIterationResult.

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

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
BqmlIterationResult()

Method Summary

Modifier and Type	Method and Description
BqmlIterationResult	clone()
Long	getDurationMs() [Output-only, Beta] Time taken to run the training iteration in milliseconds.
Double	getEvalLoss() [Output-only, Beta] Eval loss computed on the eval data at the end of the iteration.
Integer	getIndex() [Output-only, Beta] Index of the ML training iteration, starting from zero for each training run.
Double	getLearnRate() [Output-only, Beta] Learning rate used for this iteration, it varies for different training iterations if learn_rate_strategy option is not constant.
Double	getTrainingLoss() [Output-only, Beta] Training loss computed on the training data at the end of the iteration.
BqmlIterationResult	set(String fieldName, Object value)
BqmlIterationResult	setDurationMs(Long durationMs) [Output-only, Beta] Time taken to run the training iteration in milliseconds.
BqmlIterationResult	setEvalLoss(Double evalLoss) [Output-only, Beta] Eval loss computed on the eval data at the end of the iteration.
BqmlIterationResult	setIndex(Integer index) [Output-only, Beta] Index of the ML training iteration, starting from zero for each training run.
BqmlIterationResult	setLearnRate(Double learnRate) [Output-only, Beta] Learning rate used for this iteration, it varies for different training iterations if learn_rate_strategy option is not constant.
BqmlIterationResult	setTrainingLoss(Double trainingLoss) [Output-only, Beta] Training loss computed on the training data at the end of the iteration.

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

BqmlIterationResult

public BqmlIterationResult()

Method Detail

getDurationMs

public Long getDurationMs()

[Output-only, Beta] Time taken to run the training iteration in milliseconds.

Returns:

value or null for none

setDurationMs

public BqmlIterationResult setDurationMs(Long durationMs)

[Output-only, Beta] Time taken to run the training iteration in milliseconds.

Parameters:

durationMs - durationMs or null for none

getEvalLoss

public Double getEvalLoss()

[Output-only, Beta] Eval loss computed on the eval data at the end of the iteration. The eval loss is used for early stopping to avoid overfitting. No eval loss if eval_split_method option is specified as no_split or auto_split with input data size less than 500 rows.

Returns:

value or null for none

setEvalLoss

public BqmlIterationResult setEvalLoss(Double evalLoss)

[Output-only, Beta] Eval loss computed on the eval data at the end of the iteration. The eval loss is used for early stopping to avoid overfitting. No eval loss if eval_split_method option is specified as no_split or auto_split with input data size less than 500 rows.

Parameters:

evalLoss - evalLoss or null for none

getIndex

public Integer getIndex()

[Output-only, Beta] Index of the ML training iteration, starting from zero for each training run.

Returns:

value or null for none

setIndex

public BqmlIterationResult setIndex(Integer index)

[Output-only, Beta] Index of the ML training iteration, starting from zero for each training run.

Parameters:

index - index or null for none

getLearnRate

public Double getLearnRate()

[Output-only, Beta] Learning rate used for this iteration, it varies for different training iterations if learn_rate_strategy option is not constant.

Returns:

value or null for none

setLearnRate

public BqmlIterationResult setLearnRate(Double learnRate)

[Output-only, Beta] Learning rate used for this iteration, it varies for different training iterations if learn_rate_strategy option is not constant.

Parameters:

learnRate - learnRate or null for none

getTrainingLoss

public Double getTrainingLoss()

[Output-only, Beta] Training loss computed on the training data at the end of the iteration. The training loss function is defined by model type.

Returns:

value or null for none

setTrainingLoss

public BqmlIterationResult setTrainingLoss(Double trainingLoss)

[Output-only, Beta] Training loss computed on the training data at the end of the iteration. The training loss function is defined by model type.

Parameters:

trainingLoss - trainingLoss or null for none

set

public BqmlIterationResult set(String fieldName,
                               Object value)

Overrides:

set in class GenericJson

clone

public BqmlIterationResult clone()

Overrides:

clone in class GenericJson