HparamSearchSpaces (BigQuery API v2-rev20240323-2.0.0)

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.HparamSearchSpaces

All Implemented Interfaces:

Cloneable, Map<String,Object>
```
public final class HparamSearchSpaces
extends com.google.api.client.json.GenericJson
```
Hyperparameter search spaces. These should be a subset of training_options.
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

HparamSearchSpaces()

Constructors
Constructor and Description
`HparamSearchSpaces()`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`HparamSearchSpaces`	`clone()`
`StringHparamSearchSpace`	`getActivationFn()` Activation functions of neural network models.
`IntHparamSearchSpace`	`getBatchSize()` Mini batch sample size.
`StringHparamSearchSpace`	`getBoosterType()` Booster type for boosted tree models.
`DoubleHparamSearchSpace`	`getColsampleBylevel()` Subsample ratio of columns for each level for boosted tree models.
`DoubleHparamSearchSpace`	`getColsampleBynode()` Subsample ratio of columns for each node(split) for boosted tree models.
`DoubleHparamSearchSpace`	`getColsampleBytree()` Subsample ratio of columns when constructing each tree for boosted tree models.
`StringHparamSearchSpace`	`getDartNormalizeType()` Dart normalization type for boosted tree models.
`DoubleHparamSearchSpace`	`getDropout()` Dropout probability for dnn model training and boosted tree models using dart booster.
`IntArrayHparamSearchSpace`	`getHiddenUnits()` Hidden units for neural network models.
`DoubleHparamSearchSpace`	`getL1Reg()` L1 regularization coefficient.
`DoubleHparamSearchSpace`	`getL2Reg()` L2 regularization coefficient.
`DoubleHparamSearchSpace`	`getLearnRate()` Learning rate of training jobs.
`IntHparamSearchSpace`	`getMaxTreeDepth()` Maximum depth of a tree for boosted tree models.
`DoubleHparamSearchSpace`	`getMinSplitLoss()` Minimum split loss for boosted tree models.
`IntHparamSearchSpace`	`getMinTreeChildWeight()` Minimum sum of instance weight needed in a child for boosted tree models.
`IntHparamSearchSpace`	`getNumClusters()` Number of clusters for k-means.
`IntHparamSearchSpace`	`getNumFactors()` Number of latent factors to train on.
`IntHparamSearchSpace`	`getNumParallelTree()` Number of parallel trees for boosted tree models.
`StringHparamSearchSpace`	`getOptimizer()` Optimizer of TF models.
`DoubleHparamSearchSpace`	`getSubsample()` Subsample the training data to grow tree to prevent overfitting for boosted tree models.
`StringHparamSearchSpace`	`getTreeMethod()` Tree construction algorithm for boosted tree models.
`DoubleHparamSearchSpace`	`getWalsAlpha()` Hyperparameter for matrix factoration when implicit feedback type is specified.
`HparamSearchSpaces`	`set(String fieldName, Object value)`
`HparamSearchSpaces`	`setActivationFn(StringHparamSearchSpace activationFn)` Activation functions of neural network models.
`HparamSearchSpaces`	`setBatchSize(IntHparamSearchSpace batchSize)` Mini batch sample size.
`HparamSearchSpaces`	`setBoosterType(StringHparamSearchSpace boosterType)` Booster type for boosted tree models.
`HparamSearchSpaces`	`setColsampleBylevel(DoubleHparamSearchSpace colsampleBylevel)` Subsample ratio of columns for each level for boosted tree models.
`HparamSearchSpaces`	`setColsampleBynode(DoubleHparamSearchSpace colsampleBynode)` Subsample ratio of columns for each node(split) for boosted tree models.
`HparamSearchSpaces`	`setColsampleBytree(DoubleHparamSearchSpace colsampleBytree)` Subsample ratio of columns when constructing each tree for boosted tree models.
`HparamSearchSpaces`	`setDartNormalizeType(StringHparamSearchSpace dartNormalizeType)` Dart normalization type for boosted tree models.
`HparamSearchSpaces`	`setDropout(DoubleHparamSearchSpace dropout)` Dropout probability for dnn model training and boosted tree models using dart booster.
`HparamSearchSpaces`	`setHiddenUnits(IntArrayHparamSearchSpace hiddenUnits)` Hidden units for neural network models.
`HparamSearchSpaces`	`setL1Reg(DoubleHparamSearchSpace l1Reg)` L1 regularization coefficient.
`HparamSearchSpaces`	`setL2Reg(DoubleHparamSearchSpace l2Reg)` L2 regularization coefficient.
`HparamSearchSpaces`	`setLearnRate(DoubleHparamSearchSpace learnRate)` Learning rate of training jobs.
`HparamSearchSpaces`	`setMaxTreeDepth(IntHparamSearchSpace maxTreeDepth)` Maximum depth of a tree for boosted tree models.
`HparamSearchSpaces`	`setMinSplitLoss(DoubleHparamSearchSpace minSplitLoss)` Minimum split loss for boosted tree models.
`HparamSearchSpaces`	`setMinTreeChildWeight(IntHparamSearchSpace minTreeChildWeight)` Minimum sum of instance weight needed in a child for boosted tree models.
`HparamSearchSpaces`	`setNumClusters(IntHparamSearchSpace numClusters)` Number of clusters for k-means.
`HparamSearchSpaces`	`setNumFactors(IntHparamSearchSpace numFactors)` Number of latent factors to train on.
`HparamSearchSpaces`	`setNumParallelTree(IntHparamSearchSpace numParallelTree)` Number of parallel trees for boosted tree models.
`HparamSearchSpaces`	`setOptimizer(StringHparamSearchSpace optimizer)` Optimizer of TF models.
`HparamSearchSpaces`	`setSubsample(DoubleHparamSearchSpace subsample)` Subsample the training data to grow tree to prevent overfitting for boosted tree models.
`HparamSearchSpaces`	`setTreeMethod(StringHparamSearchSpace treeMethod)` Tree construction algorithm for boosted tree models.
`HparamSearchSpaces`	`setWalsAlpha(DoubleHparamSearchSpace walsAlpha)` Hyperparameter for matrix factoration when implicit feedback type is specified.

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
  - HparamSearchSpaces
```
public HparamSearchSpaces()
```
- Method Detail
  - getActivationFn
```
public StringHparamSearchSpace getActivationFn()
```
    Activation functions of neural network models.
    
    Returns:
    
    value or null for none
  - setActivationFn
```
public HparamSearchSpaces setActivationFn(StringHparamSearchSpace activationFn)
```
    Activation functions of neural network models.
    
    Parameters:
    
    activationFn - activationFn or null for none
  - getBatchSize
```
public IntHparamSearchSpace getBatchSize()
```
    Mini batch sample size.
    
    Returns:
    
    value or null for none
  - setBatchSize
```
public HparamSearchSpaces setBatchSize(IntHparamSearchSpace batchSize)
```
    Mini batch sample size.
    
    Parameters:
    
    batchSize - batchSize or null for none
  - getBoosterType
```
public StringHparamSearchSpace getBoosterType()
```
    Booster type for boosted tree models.
    
    Returns:
    
    value or null for none
  - setBoosterType
```
public HparamSearchSpaces setBoosterType(StringHparamSearchSpace boosterType)
```
    Booster type for boosted tree models.
    
    Parameters:
    
    boosterType - boosterType or null for none
  - getColsampleBylevel
```
public DoubleHparamSearchSpace getColsampleBylevel()
```
    Subsample ratio of columns for each level for boosted tree models.
    
    Returns:
    
    value or null for none
  - setColsampleBylevel
```
public HparamSearchSpaces setColsampleBylevel(DoubleHparamSearchSpace colsampleBylevel)
```
    Subsample ratio of columns for each level for boosted tree models.
    
    Parameters:
    
    colsampleBylevel - colsampleBylevel or null for none
  - getColsampleBynode
```
public DoubleHparamSearchSpace getColsampleBynode()
```
    Subsample ratio of columns for each node(split) for boosted tree models.
    
    Returns:
    
    value or null for none
  - setColsampleBynode
```
public HparamSearchSpaces setColsampleBynode(DoubleHparamSearchSpace colsampleBynode)
```
    Subsample ratio of columns for each node(split) for boosted tree models.
    
    Parameters:
    
    colsampleBynode - colsampleBynode or null for none
  - getColsampleBytree
```
public DoubleHparamSearchSpace getColsampleBytree()
```
    Subsample ratio of columns when constructing each tree for boosted tree models.
    
    Returns:
    
    value or null for none
  - setColsampleBytree
```
public HparamSearchSpaces setColsampleBytree(DoubleHparamSearchSpace colsampleBytree)
```
    Subsample ratio of columns when constructing each tree for boosted tree models.
    
    Parameters:
    
    colsampleBytree - colsampleBytree or null for none
  - getDartNormalizeType
```
public StringHparamSearchSpace getDartNormalizeType()
```
    Dart normalization type for boosted tree models.
    
    Returns:
    
    value or null for none
  - setDartNormalizeType
```
public HparamSearchSpaces setDartNormalizeType(StringHparamSearchSpace dartNormalizeType)
```
    Dart normalization type for boosted tree models.
    
    Parameters:
    
    dartNormalizeType - dartNormalizeType or null for none
  - getDropout
```
public DoubleHparamSearchSpace getDropout()
```
    Dropout probability for dnn model training and boosted tree models using dart booster.
    
    Returns:
    
    value or null for none
  - setDropout
```
public HparamSearchSpaces setDropout(DoubleHparamSearchSpace dropout)
```
    Dropout probability for dnn model training and boosted tree models using dart booster.
    
    Parameters:
    
    dropout - dropout or null for none
  - getHiddenUnits
```
public IntArrayHparamSearchSpace getHiddenUnits()
```
    Hidden units for neural network models.
    
    Returns:
    
    value or null for none
  - setHiddenUnits
```
public HparamSearchSpaces setHiddenUnits(IntArrayHparamSearchSpace hiddenUnits)
```
    Hidden units for neural network models.
    
    Parameters:
    
    hiddenUnits - hiddenUnits or null for none
  - getL1Reg
```
public DoubleHparamSearchSpace getL1Reg()
```
    L1 regularization coefficient.
    
    Returns:
    
    value or null for none
  - setL1Reg
```
public HparamSearchSpaces setL1Reg(DoubleHparamSearchSpace l1Reg)
```
    L1 regularization coefficient.
    
    Parameters:
    
    l1Reg - l1Reg or null for none
  - getL2Reg
```
public DoubleHparamSearchSpace getL2Reg()
```
    L2 regularization coefficient.
    
    Returns:
    
    value or null for none
  - setL2Reg
```
public HparamSearchSpaces setL2Reg(DoubleHparamSearchSpace l2Reg)
```
    L2 regularization coefficient.
    
    Parameters:
    
    l2Reg - l2Reg or null for none
  - getLearnRate
```
public DoubleHparamSearchSpace getLearnRate()
```
    Learning rate of training jobs.
    
    Returns:
    
    value or null for none
  - setLearnRate
```
public HparamSearchSpaces setLearnRate(DoubleHparamSearchSpace learnRate)
```
    Learning rate of training jobs.
    
    Parameters:
    
    learnRate - learnRate or null for none
  - getMaxTreeDepth
```
public IntHparamSearchSpace getMaxTreeDepth()
```
    Maximum depth of a tree for boosted tree models.
    
    Returns:
    
    value or null for none
  - setMaxTreeDepth
```
public HparamSearchSpaces setMaxTreeDepth(IntHparamSearchSpace maxTreeDepth)
```
    Maximum depth of a tree for boosted tree models.
    
    Parameters:
    
    maxTreeDepth - maxTreeDepth or null for none
  - getMinSplitLoss
```
public DoubleHparamSearchSpace getMinSplitLoss()
```
    Minimum split loss for boosted tree models.
    
    Returns:
    
    value or null for none
  - setMinSplitLoss
```
public HparamSearchSpaces setMinSplitLoss(DoubleHparamSearchSpace minSplitLoss)
```
    Minimum split loss for boosted tree models.
    
    Parameters:
    
    minSplitLoss - minSplitLoss or null for none
  - getMinTreeChildWeight
```
public IntHparamSearchSpace getMinTreeChildWeight()
```
    Minimum sum of instance weight needed in a child for boosted tree models.
    
    Returns:
    
    value or null for none
  - setMinTreeChildWeight
```
public HparamSearchSpaces setMinTreeChildWeight(IntHparamSearchSpace minTreeChildWeight)
```
    Minimum sum of instance weight needed in a child for boosted tree models.
    
    Parameters:
    
    minTreeChildWeight - minTreeChildWeight or null for none
  - getNumClusters
```
public IntHparamSearchSpace getNumClusters()
```
    Number of clusters for k-means.
    
    Returns:
    
    value or null for none
  - setNumClusters
```
public HparamSearchSpaces setNumClusters(IntHparamSearchSpace numClusters)
```
    Number of clusters for k-means.
    
    Parameters:
    
    numClusters - numClusters or null for none
  - getNumFactors
```
public IntHparamSearchSpace getNumFactors()
```
    Number of latent factors to train on.
    
    Returns:
    
    value or null for none
  - setNumFactors
```
public HparamSearchSpaces setNumFactors(IntHparamSearchSpace numFactors)
```
    Number of latent factors to train on.
    
    Parameters:
    
    numFactors - numFactors or null for none
  - getNumParallelTree
```
public IntHparamSearchSpace getNumParallelTree()
```
    Number of parallel trees for boosted tree models.
    
    Returns:
    
    value or null for none
  - setNumParallelTree
```
public HparamSearchSpaces setNumParallelTree(IntHparamSearchSpace numParallelTree)
```
    Number of parallel trees for boosted tree models.
    
    Parameters:
    
    numParallelTree - numParallelTree or null for none
  - getOptimizer
```
public StringHparamSearchSpace getOptimizer()
```
    Optimizer of TF models.
    
    Returns:
    
    value or null for none
  - setOptimizer
```
public HparamSearchSpaces setOptimizer(StringHparamSearchSpace optimizer)
```
    Optimizer of TF models.
    
    Parameters:
    
    optimizer - optimizer or null for none
  - getSubsample
```
public DoubleHparamSearchSpace getSubsample()
```
    Subsample the training data to grow tree to prevent overfitting for boosted tree models.
    
    Returns:
    
    value or null for none
  - setSubsample
```
public HparamSearchSpaces setSubsample(DoubleHparamSearchSpace subsample)
```
    Subsample the training data to grow tree to prevent overfitting for boosted tree models.
    
    Parameters:
    
    subsample - subsample or null for none
  - getTreeMethod
```
public StringHparamSearchSpace getTreeMethod()
```
    Tree construction algorithm for boosted tree models.
    
    Returns:
    
    value or null for none
  - setTreeMethod
```
public HparamSearchSpaces setTreeMethod(StringHparamSearchSpace treeMethod)
```
    Tree construction algorithm for boosted tree models.
    
    Parameters:
    
    treeMethod - treeMethod or null for none
  - getWalsAlpha
```
public DoubleHparamSearchSpace getWalsAlpha()
```
    Hyperparameter for matrix factoration when implicit feedback type is specified.
    
    Returns:
    
    value or null for none
  - setWalsAlpha
```
public HparamSearchSpaces setWalsAlpha(DoubleHparamSearchSpace walsAlpha)
```
    Hyperparameter for matrix factoration when implicit feedback type is specified.
    
    Parameters:
    
    walsAlpha - walsAlpha or null for none
  - set
```
public HparamSearchSpaces set(String fieldName,
                              Object value)
```
    Overrides:
    
    set in class com.google.api.client.json.GenericJson
  - clone
```
public HparamSearchSpaces clone()
```
    Overrides:
    
    clone in class com.google.api.client.json.GenericJson

Class HparamSearchSpaces

Nested Class Summary

Nested classes/interfaces inherited from class com.google.api.client.util.GenericData

Nested classes/interfaces inherited from class java.util.AbstractMap

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

Constructor Summary

Method Summary

Methods inherited from class com.google.api.client.json.GenericJson

Methods inherited from class com.google.api.client.util.GenericData

Methods inherited from class java.util.AbstractMap

Methods inherited from class java.lang.Object

Methods inherited from interface java.util.Map

Constructor Detail

HparamSearchSpaces

Method Detail

getActivationFn

setActivationFn

getBatchSize

setBatchSize

getBoosterType

setBoosterType

getColsampleBylevel

setColsampleBylevel

getColsampleBynode

setColsampleBynode

getColsampleBytree

setColsampleBytree

getDartNormalizeType

setDartNormalizeType

getDropout

setDropout

getHiddenUnits

setHiddenUnits

getL1Reg

setL1Reg

getL2Reg

setL2Reg

getLearnRate

setLearnRate

getMaxTreeDepth

setMaxTreeDepth

getMinSplitLoss

setMinSplitLoss

getMinTreeChildWeight

setMinTreeChildWeight

getNumClusters

setNumClusters

getNumFactors

setNumFactors

getNumParallelTree

setNumParallelTree

getOptimizer

setOptimizer

getSubsample

setSubsample

getTreeMethod

setTreeMethod

getWalsAlpha

setWalsAlpha

set

clone