com.google.api.services.bigquery.model

Class IterationResult

java.lang.Object

java.util.AbstractMap<java.lang.String,java.lang.Object>

com.google.api.client.util.GenericData

com.google.api.client.json.GenericJson

com.google.api.services.bigquery.model.IterationResult

All Implemented Interfaces:

java.lang.Cloneable, java.util.Map<java.lang.String,java.lang.Object>

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

Model definition for IterationResult.

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

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

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

java.util.Map.Entry<K,V>

Constructor Summary

Constructors

Constructor and Description
IterationResult()

Method Summary

Modifier and Type	Method and Description
IterationResult	clone()
java.lang.Long	getDurationMs() [Output-only, Beta] Time taken to run the training iteration in milliseconds.
java.lang.Double	getEvalLoss() [Output-only, Beta] Eval loss computed on the eval data at the end of the iteration.
java.lang.Integer	getIndex() [Output-only, Beta] Index of the ML training iteration, starting from zero for each training run.
java.lang.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.
java.lang.Double	getTrainingLoss() [Output-only, Beta] Training loss computed on the training data at the end of the iteration.
IterationResult	set(java.lang.String fieldName, java.lang.Object value)
IterationResult	setDurationMs(java.lang.Long durationMs) [Output-only, Beta] Time taken to run the training iteration in milliseconds.
IterationResult	setEvalLoss(java.lang.Double evalLoss) [Output-only, Beta] Eval loss computed on the eval data at the end of the iteration.
IterationResult	setIndex(java.lang.Integer index) [Output-only, Beta] Index of the ML training iteration, starting from zero for each training run.
IterationResult	setLearnRate(java.lang.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.
IterationResult	setTrainingLoss(java.lang.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, get, getClassInfo, getUnknownKeys, put, putAll, remove, setUnknownKeys

Methods inherited from class java.util.AbstractMap

clear, containsKey, containsValue, equals, hashCode, 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

IterationResult

public IterationResult()

Method Detail

getDurationMs

public java.lang.Long getDurationMs()

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

Returns:

value or null for none

setDurationMs

public IterationResult setDurationMs(java.lang.Long durationMs)

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

Parameters:

durationMs - durationMs or null for none

getEvalLoss

public java.lang.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 IterationResult setEvalLoss(java.lang.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 java.lang.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 IterationResult setIndex(java.lang.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 java.lang.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 IterationResult setLearnRate(java.lang.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 java.lang.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 IterationResult setTrainingLoss(java.lang.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 IterationResult set(java.lang.String fieldName,
                           java.lang.Object value)

Overrides:

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

clone

public IterationResult clone()

Overrides:

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