com.google.api.services.bigquery.model.HparamSearchSpaces Maven / Gradle / Ivy
/*
* Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except
* in compliance with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software distributed under the License
* is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
* or implied. See the License for the specific language governing permissions and limitations under
* the License.
*/
/*
* This code was generated by https://github.com/googleapis/google-api-java-client-services/
* Modify at your own risk.
*/
package com.google.api.services.bigquery.model;
/**
* 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.
*/
@SuppressWarnings("javadoc")
public final class HparamSearchSpaces extends com.google.api.client.json.GenericJson {
/**
* Activation functions of neural network models.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private StringHparamSearchSpace activationFn;
/**
* Mini batch sample size.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private IntHparamSearchSpace batchSize;
/**
* Booster type for boosted tree models.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private StringHparamSearchSpace boosterType;
/**
* Subsample ratio of columns for each level for boosted tree models.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private DoubleHparamSearchSpace colsampleBylevel;
/**
* Subsample ratio of columns for each node(split) for boosted tree models.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private DoubleHparamSearchSpace colsampleBynode;
/**
* Subsample ratio of columns when constructing each tree for boosted tree models.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private DoubleHparamSearchSpace colsampleBytree;
/**
* Dart normalization type for boosted tree models.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private StringHparamSearchSpace dartNormalizeType;
/**
* Dropout probability for dnn model training and boosted tree models using dart booster.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private DoubleHparamSearchSpace dropout;
/**
* Hidden units for neural network models.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private IntArrayHparamSearchSpace hiddenUnits;
/**
* L1 regularization coefficient.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private DoubleHparamSearchSpace l1Reg;
/**
* L2 regularization coefficient.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private DoubleHparamSearchSpace l2Reg;
/**
* Learning rate of training jobs.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private DoubleHparamSearchSpace learnRate;
/**
* Maximum depth of a tree for boosted tree models.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private IntHparamSearchSpace maxTreeDepth;
/**
* Minimum split loss for boosted tree models.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private DoubleHparamSearchSpace minSplitLoss;
/**
* Minimum sum of instance weight needed in a child for boosted tree models.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private IntHparamSearchSpace minTreeChildWeight;
/**
* Number of clusters for k-means.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private IntHparamSearchSpace numClusters;
/**
* Number of latent factors to train on.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private IntHparamSearchSpace numFactors;
/**
* Number of parallel trees for boosted tree models.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private IntHparamSearchSpace numParallelTree;
/**
* Optimizer of TF models.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private StringHparamSearchSpace optimizer;
/**
* Subsample the training data to grow tree to prevent overfitting for boosted tree models.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private DoubleHparamSearchSpace subsample;
/**
* Tree construction algorithm for boosted tree models.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private StringHparamSearchSpace treeMethod;
/**
* Hyperparameter for matrix factoration when implicit feedback type is specified.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private DoubleHparamSearchSpace walsAlpha;
/**
* Activation functions of neural network models.
* @return value or {@code null} for none
*/
public StringHparamSearchSpace getActivationFn() {
return activationFn;
}
/**
* Activation functions of neural network models.
* @param activationFn activationFn or {@code null} for none
*/
public HparamSearchSpaces setActivationFn(StringHparamSearchSpace activationFn) {
this.activationFn = activationFn;
return this;
}
/**
* Mini batch sample size.
* @return value or {@code null} for none
*/
public IntHparamSearchSpace getBatchSize() {
return batchSize;
}
/**
* Mini batch sample size.
* @param batchSize batchSize or {@code null} for none
*/
public HparamSearchSpaces setBatchSize(IntHparamSearchSpace batchSize) {
this.batchSize = batchSize;
return this;
}
/**
* Booster type for boosted tree models.
* @return value or {@code null} for none
*/
public StringHparamSearchSpace getBoosterType() {
return boosterType;
}
/**
* Booster type for boosted tree models.
* @param boosterType boosterType or {@code null} for none
*/
public HparamSearchSpaces setBoosterType(StringHparamSearchSpace boosterType) {
this.boosterType = boosterType;
return this;
}
/**
* Subsample ratio of columns for each level for boosted tree models.
* @return value or {@code null} for none
*/
public DoubleHparamSearchSpace getColsampleBylevel() {
return colsampleBylevel;
}
/**
* Subsample ratio of columns for each level for boosted tree models.
* @param colsampleBylevel colsampleBylevel or {@code null} for none
*/
public HparamSearchSpaces setColsampleBylevel(DoubleHparamSearchSpace colsampleBylevel) {
this.colsampleBylevel = colsampleBylevel;
return this;
}
/**
* Subsample ratio of columns for each node(split) for boosted tree models.
* @return value or {@code null} for none
*/
public DoubleHparamSearchSpace getColsampleBynode() {
return colsampleBynode;
}
/**
* Subsample ratio of columns for each node(split) for boosted tree models.
* @param colsampleBynode colsampleBynode or {@code null} for none
*/
public HparamSearchSpaces setColsampleBynode(DoubleHparamSearchSpace colsampleBynode) {
this.colsampleBynode = colsampleBynode;
return this;
}
/**
* Subsample ratio of columns when constructing each tree for boosted tree models.
* @return value or {@code null} for none
*/
public DoubleHparamSearchSpace getColsampleBytree() {
return colsampleBytree;
}
/**
* Subsample ratio of columns when constructing each tree for boosted tree models.
* @param colsampleBytree colsampleBytree or {@code null} for none
*/
public HparamSearchSpaces setColsampleBytree(DoubleHparamSearchSpace colsampleBytree) {
this.colsampleBytree = colsampleBytree;
return this;
}
/**
* Dart normalization type for boosted tree models.
* @return value or {@code null} for none
*/
public StringHparamSearchSpace getDartNormalizeType() {
return dartNormalizeType;
}
/**
* Dart normalization type for boosted tree models.
* @param dartNormalizeType dartNormalizeType or {@code null} for none
*/
public HparamSearchSpaces setDartNormalizeType(StringHparamSearchSpace dartNormalizeType) {
this.dartNormalizeType = dartNormalizeType;
return this;
}
/**
* Dropout probability for dnn model training and boosted tree models using dart booster.
* @return value or {@code null} for none
*/
public DoubleHparamSearchSpace getDropout() {
return dropout;
}
/**
* Dropout probability for dnn model training and boosted tree models using dart booster.
* @param dropout dropout or {@code null} for none
*/
public HparamSearchSpaces setDropout(DoubleHparamSearchSpace dropout) {
this.dropout = dropout;
return this;
}
/**
* Hidden units for neural network models.
* @return value or {@code null} for none
*/
public IntArrayHparamSearchSpace getHiddenUnits() {
return hiddenUnits;
}
/**
* Hidden units for neural network models.
* @param hiddenUnits hiddenUnits or {@code null} for none
*/
public HparamSearchSpaces setHiddenUnits(IntArrayHparamSearchSpace hiddenUnits) {
this.hiddenUnits = hiddenUnits;
return this;
}
/**
* L1 regularization coefficient.
* @return value or {@code null} for none
*/
public DoubleHparamSearchSpace getL1Reg() {
return l1Reg;
}
/**
* L1 regularization coefficient.
* @param l1Reg l1Reg or {@code null} for none
*/
public HparamSearchSpaces setL1Reg(DoubleHparamSearchSpace l1Reg) {
this.l1Reg = l1Reg;
return this;
}
/**
* L2 regularization coefficient.
* @return value or {@code null} for none
*/
public DoubleHparamSearchSpace getL2Reg() {
return l2Reg;
}
/**
* L2 regularization coefficient.
* @param l2Reg l2Reg or {@code null} for none
*/
public HparamSearchSpaces setL2Reg(DoubleHparamSearchSpace l2Reg) {
this.l2Reg = l2Reg;
return this;
}
/**
* Learning rate of training jobs.
* @return value or {@code null} for none
*/
public DoubleHparamSearchSpace getLearnRate() {
return learnRate;
}
/**
* Learning rate of training jobs.
* @param learnRate learnRate or {@code null} for none
*/
public HparamSearchSpaces setLearnRate(DoubleHparamSearchSpace learnRate) {
this.learnRate = learnRate;
return this;
}
/**
* Maximum depth of a tree for boosted tree models.
* @return value or {@code null} for none
*/
public IntHparamSearchSpace getMaxTreeDepth() {
return maxTreeDepth;
}
/**
* Maximum depth of a tree for boosted tree models.
* @param maxTreeDepth maxTreeDepth or {@code null} for none
*/
public HparamSearchSpaces setMaxTreeDepth(IntHparamSearchSpace maxTreeDepth) {
this.maxTreeDepth = maxTreeDepth;
return this;
}
/**
* Minimum split loss for boosted tree models.
* @return value or {@code null} for none
*/
public DoubleHparamSearchSpace getMinSplitLoss() {
return minSplitLoss;
}
/**
* Minimum split loss for boosted tree models.
* @param minSplitLoss minSplitLoss or {@code null} for none
*/
public HparamSearchSpaces setMinSplitLoss(DoubleHparamSearchSpace minSplitLoss) {
this.minSplitLoss = minSplitLoss;
return this;
}
/**
* Minimum sum of instance weight needed in a child for boosted tree models.
* @return value or {@code null} for none
*/
public IntHparamSearchSpace getMinTreeChildWeight() {
return minTreeChildWeight;
}
/**
* Minimum sum of instance weight needed in a child for boosted tree models.
* @param minTreeChildWeight minTreeChildWeight or {@code null} for none
*/
public HparamSearchSpaces setMinTreeChildWeight(IntHparamSearchSpace minTreeChildWeight) {
this.minTreeChildWeight = minTreeChildWeight;
return this;
}
/**
* Number of clusters for k-means.
* @return value or {@code null} for none
*/
public IntHparamSearchSpace getNumClusters() {
return numClusters;
}
/**
* Number of clusters for k-means.
* @param numClusters numClusters or {@code null} for none
*/
public HparamSearchSpaces setNumClusters(IntHparamSearchSpace numClusters) {
this.numClusters = numClusters;
return this;
}
/**
* Number of latent factors to train on.
* @return value or {@code null} for none
*/
public IntHparamSearchSpace getNumFactors() {
return numFactors;
}
/**
* Number of latent factors to train on.
* @param numFactors numFactors or {@code null} for none
*/
public HparamSearchSpaces setNumFactors(IntHparamSearchSpace numFactors) {
this.numFactors = numFactors;
return this;
}
/**
* Number of parallel trees for boosted tree models.
* @return value or {@code null} for none
*/
public IntHparamSearchSpace getNumParallelTree() {
return numParallelTree;
}
/**
* Number of parallel trees for boosted tree models.
* @param numParallelTree numParallelTree or {@code null} for none
*/
public HparamSearchSpaces setNumParallelTree(IntHparamSearchSpace numParallelTree) {
this.numParallelTree = numParallelTree;
return this;
}
/**
* Optimizer of TF models.
* @return value or {@code null} for none
*/
public StringHparamSearchSpace getOptimizer() {
return optimizer;
}
/**
* Optimizer of TF models.
* @param optimizer optimizer or {@code null} for none
*/
public HparamSearchSpaces setOptimizer(StringHparamSearchSpace optimizer) {
this.optimizer = optimizer;
return this;
}
/**
* Subsample the training data to grow tree to prevent overfitting for boosted tree models.
* @return value or {@code null} for none
*/
public DoubleHparamSearchSpace getSubsample() {
return subsample;
}
/**
* Subsample the training data to grow tree to prevent overfitting for boosted tree models.
* @param subsample subsample or {@code null} for none
*/
public HparamSearchSpaces setSubsample(DoubleHparamSearchSpace subsample) {
this.subsample = subsample;
return this;
}
/**
* Tree construction algorithm for boosted tree models.
* @return value or {@code null} for none
*/
public StringHparamSearchSpace getTreeMethod() {
return treeMethod;
}
/**
* Tree construction algorithm for boosted tree models.
* @param treeMethod treeMethod or {@code null} for none
*/
public HparamSearchSpaces setTreeMethod(StringHparamSearchSpace treeMethod) {
this.treeMethod = treeMethod;
return this;
}
/**
* Hyperparameter for matrix factoration when implicit feedback type is specified.
* @return value or {@code null} for none
*/
public DoubleHparamSearchSpace getWalsAlpha() {
return walsAlpha;
}
/**
* Hyperparameter for matrix factoration when implicit feedback type is specified.
* @param walsAlpha walsAlpha or {@code null} for none
*/
public HparamSearchSpaces setWalsAlpha(DoubleHparamSearchSpace walsAlpha) {
this.walsAlpha = walsAlpha;
return this;
}
@Override
public HparamSearchSpaces set(String fieldName, Object value) {
return (HparamSearchSpaces) super.set(fieldName, value);
}
@Override
public HparamSearchSpaces clone() {
return (HparamSearchSpaces) super.clone();
}
}