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BqmlIterationResult (BigQuery API v2-rev20190423-1.28.0)











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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 com.google.api.client.json.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
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


BqmlIterationResult() 









Method Summary

All Methods Instance Methods Concrete Methods 

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, 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





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 com.google.api.client.json.GenericJson








clone
public BqmlIterationResult clone()

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














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Copyright © 2011–2019 Google. All rights reserved.

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.