public final class TrainingOptions extends GenericJson
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
GenericData.Flags
AbstractMap.SimpleEntry<K,V>, AbstractMap.SimpleImmutableEntry<K,V>
Constructor and Description |
---|
TrainingOptions() |
Modifier and Type | Method and Description |
---|---|
TrainingOptions |
clone() |
Boolean |
getAutoArima()
Whether to enable auto ARIMA or not.
|
Long |
getAutoArimaMaxOrder()
The max value of non-seasonal p and q.
|
Long |
getBatchSize()
Batch size for dnn models.
|
String |
getDataFrequency()
The data frequency of a time series.
|
String |
getDataSplitColumn()
The column to split data with.
|
Double |
getDataSplitEvalFraction()
The fraction of evaluation data over the whole input data.
|
String |
getDataSplitMethod()
The data split type for training and evaluation, e.g.
|
String |
getDistanceType()
Distance type for clustering models.
|
Double |
getDropout()
Dropout probability for dnn models.
|
Boolean |
getEarlyStop()
Whether to stop early when the loss doesn't improve significantly any more (compared to
min_relative_progress).
|
String |
getFeedbackType()
Feedback type that specifies which algorithm to run for matrix factorization.
|
List<Long> |
getHiddenUnits()
Hidden units for dnn models.
|
String |
getHolidayRegion()
The geographical region based on which the holidays are considered in time series modeling.
|
Long |
getHorizon()
The number of periods ahead that need to be forecasted.
|
Boolean |
getIncludeDrift()
Include drift when fitting an ARIMA model.
|
Double |
getInitialLearnRate()
Specifies the initial learning rate for the line search learn rate strategy.
|
List<String> |
getInputLabelColumns()
Name of input label columns in training data.
|
String |
getItemColumn()
Item column specified for matrix factorization models.
|
String |
getKmeansInitializationColumn()
The column used to provide the initial centroids for kmeans algorithm when
kmeans_initialization_method is CUSTOM.
|
String |
getKmeansInitializationMethod()
The method used to initialize the centroids for kmeans algorithm.
|
Double |
getL1Regularization()
L1 regularization coefficient.
|
Double |
getL2Regularization()
L2 regularization coefficient.
|
Map<String,Double> |
getLabelClassWeights()
Weights associated with each label class, for rebalancing the training data.
|
Double |
getLearnRate()
Learning rate in training.
|
String |
getLearnRateStrategy()
The strategy to determine learn rate for the current iteration.
|
String |
getLossType()
Type of loss function used during training run.
|
Long |
getMaxIterations()
The maximum number of iterations in training.
|
Long |
getMaxTreeDepth()
Maximum depth of a tree for boosted tree models.
|
Double |
getMinRelativeProgress()
When early_stop is true, stops training when accuracy improvement is less than
'min_relative_progress'.
|
Double |
getMinSplitLoss()
Minimum split loss for boosted tree models.
|
String |
getModelUri()
Google Cloud Storage URI from which the model was imported.
|
ArimaOrder |
getNonSeasonalOrder()
A specification of the non-seasonal part of the ARIMA model: the three components (p, d, q) are
the AR order, the degree of differencing, and the MA order.
|
Long |
getNumClusters()
Number of clusters for clustering models.
|
Long |
getNumFactors()
Num factors specified for matrix factorization models.
|
String |
getOptimizationStrategy()
Optimization strategy for training linear regression models.
|
Boolean |
getPreserveInputStructs()
Whether to preserve the input structs in output feature names.
|
Double |
getSubsample()
Subsample fraction of the training data to grow tree to prevent overfitting for boosted tree
models.
|
String |
getTimeSeriesDataColumn()
Column to be designated as time series data for ARIMA model.
|
String |
getTimeSeriesIdColumn()
The time series id column that was used during ARIMA model training.
|
String |
getTimeSeriesTimestampColumn()
Column to be designated as time series timestamp for ARIMA model.
|
String |
getUserColumn()
User column specified for matrix factorization models.
|
Double |
getWalsAlpha()
Hyperparameter for matrix factoration when implicit feedback type is specified.
|
Boolean |
getWarmStart()
Whether to train a model from the last checkpoint.
|
TrainingOptions |
set(String fieldName,
Object value) |
TrainingOptions |
setAutoArima(Boolean autoArima)
Whether to enable auto ARIMA or not.
|
TrainingOptions |
setAutoArimaMaxOrder(Long autoArimaMaxOrder)
The max value of non-seasonal p and q.
|
TrainingOptions |
setBatchSize(Long batchSize)
Batch size for dnn models.
|
TrainingOptions |
setDataFrequency(String dataFrequency)
The data frequency of a time series.
|
TrainingOptions |
setDataSplitColumn(String dataSplitColumn)
The column to split data with.
|
TrainingOptions |
setDataSplitEvalFraction(Double dataSplitEvalFraction)
The fraction of evaluation data over the whole input data.
|
TrainingOptions |
setDataSplitMethod(String dataSplitMethod)
The data split type for training and evaluation, e.g.
|
TrainingOptions |
setDistanceType(String distanceType)
Distance type for clustering models.
|
TrainingOptions |
setDropout(Double dropout)
Dropout probability for dnn models.
|
TrainingOptions |
setEarlyStop(Boolean earlyStop)
Whether to stop early when the loss doesn't improve significantly any more (compared to
min_relative_progress).
|
TrainingOptions |
setFeedbackType(String feedbackType)
Feedback type that specifies which algorithm to run for matrix factorization.
|
TrainingOptions |
setHiddenUnits(List<Long> hiddenUnits)
Hidden units for dnn models.
|
TrainingOptions |
setHolidayRegion(String holidayRegion)
The geographical region based on which the holidays are considered in time series modeling.
|
TrainingOptions |
setHorizon(Long horizon)
The number of periods ahead that need to be forecasted.
|
TrainingOptions |
setIncludeDrift(Boolean includeDrift)
Include drift when fitting an ARIMA model.
|
TrainingOptions |
setInitialLearnRate(Double initialLearnRate)
Specifies the initial learning rate for the line search learn rate strategy.
|
TrainingOptions |
setInputLabelColumns(List<String> inputLabelColumns)
Name of input label columns in training data.
|
TrainingOptions |
setItemColumn(String itemColumn)
Item column specified for matrix factorization models.
|
TrainingOptions |
setKmeansInitializationColumn(String kmeansInitializationColumn)
The column used to provide the initial centroids for kmeans algorithm when
kmeans_initialization_method is CUSTOM.
|
TrainingOptions |
setKmeansInitializationMethod(String kmeansInitializationMethod)
The method used to initialize the centroids for kmeans algorithm.
|
TrainingOptions |
setL1Regularization(Double l1Regularization)
L1 regularization coefficient.
|
TrainingOptions |
setL2Regularization(Double l2Regularization)
L2 regularization coefficient.
|
TrainingOptions |
setLabelClassWeights(Map<String,Double> labelClassWeights)
Weights associated with each label class, for rebalancing the training data.
|
TrainingOptions |
setLearnRate(Double learnRate)
Learning rate in training.
|
TrainingOptions |
setLearnRateStrategy(String learnRateStrategy)
The strategy to determine learn rate for the current iteration.
|
TrainingOptions |
setLossType(String lossType)
Type of loss function used during training run.
|
TrainingOptions |
setMaxIterations(Long maxIterations)
The maximum number of iterations in training.
|
TrainingOptions |
setMaxTreeDepth(Long maxTreeDepth)
Maximum depth of a tree for boosted tree models.
|
TrainingOptions |
setMinRelativeProgress(Double minRelativeProgress)
When early_stop is true, stops training when accuracy improvement is less than
'min_relative_progress'.
|
TrainingOptions |
setMinSplitLoss(Double minSplitLoss)
Minimum split loss for boosted tree models.
|
TrainingOptions |
setModelUri(String modelUri)
Google Cloud Storage URI from which the model was imported.
|
TrainingOptions |
setNonSeasonalOrder(ArimaOrder nonSeasonalOrder)
A specification of the non-seasonal part of the ARIMA model: the three components (p, d, q) are
the AR order, the degree of differencing, and the MA order.
|
TrainingOptions |
setNumClusters(Long numClusters)
Number of clusters for clustering models.
|
TrainingOptions |
setNumFactors(Long numFactors)
Num factors specified for matrix factorization models.
|
TrainingOptions |
setOptimizationStrategy(String optimizationStrategy)
Optimization strategy for training linear regression models.
|
TrainingOptions |
setPreserveInputStructs(Boolean preserveInputStructs)
Whether to preserve the input structs in output feature names.
|
TrainingOptions |
setSubsample(Double subsample)
Subsample fraction of the training data to grow tree to prevent overfitting for boosted tree
models.
|
TrainingOptions |
setTimeSeriesDataColumn(String timeSeriesDataColumn)
Column to be designated as time series data for ARIMA model.
|
TrainingOptions |
setTimeSeriesIdColumn(String timeSeriesIdColumn)
The time series id column that was used during ARIMA model training.
|
TrainingOptions |
setTimeSeriesTimestampColumn(String timeSeriesTimestampColumn)
Column to be designated as time series timestamp for ARIMA model.
|
TrainingOptions |
setUserColumn(String userColumn)
User column specified for matrix factorization models.
|
TrainingOptions |
setWalsAlpha(Double walsAlpha)
Hyperparameter for matrix factoration when implicit feedback type is specified.
|
TrainingOptions |
setWarmStart(Boolean warmStart)
Whether to train a model from the last checkpoint.
|
getFactory, setFactory, toPrettyString, toString
entrySet, equals, get, getClassInfo, getUnknownKeys, hashCode, put, putAll, remove, setUnknownKeys
clear, containsKey, containsValue, isEmpty, keySet, size, values
finalize, getClass, notify, notifyAll, wait, wait, wait
compute, computeIfAbsent, computeIfPresent, forEach, getOrDefault, merge, putIfAbsent, remove, replace, replace, replaceAll
public Boolean getAutoArima()
null
for nonepublic TrainingOptions setAutoArima(Boolean autoArima)
autoArima
- autoArima or null
for nonepublic Long getAutoArimaMaxOrder()
null
for nonepublic TrainingOptions setAutoArimaMaxOrder(Long autoArimaMaxOrder)
autoArimaMaxOrder
- autoArimaMaxOrder or null
for nonepublic Long getBatchSize()
null
for nonepublic TrainingOptions setBatchSize(Long batchSize)
batchSize
- batchSize or null
for nonepublic String getDataFrequency()
null
for nonepublic TrainingOptions setDataFrequency(String dataFrequency)
dataFrequency
- dataFrequency or null
for nonepublic String getDataSplitColumn()
null
for nonepublic TrainingOptions setDataSplitColumn(String dataSplitColumn)
dataSplitColumn
- dataSplitColumn or null
for nonepublic Double getDataSplitEvalFraction()
null
for nonepublic TrainingOptions setDataSplitEvalFraction(Double dataSplitEvalFraction)
dataSplitEvalFraction
- dataSplitEvalFraction or null
for nonepublic String getDataSplitMethod()
null
for nonepublic TrainingOptions setDataSplitMethod(String dataSplitMethod)
dataSplitMethod
- dataSplitMethod or null
for nonepublic String getDistanceType()
null
for nonepublic TrainingOptions setDistanceType(String distanceType)
distanceType
- distanceType or null
for nonepublic Double getDropout()
null
for nonepublic TrainingOptions setDropout(Double dropout)
dropout
- dropout or null
for nonepublic Boolean getEarlyStop()
null
for nonepublic TrainingOptions setEarlyStop(Boolean earlyStop)
earlyStop
- earlyStop or null
for nonepublic String getFeedbackType()
null
for nonepublic TrainingOptions setFeedbackType(String feedbackType)
feedbackType
- feedbackType or null
for nonepublic List<Long> getHiddenUnits()
null
for nonepublic TrainingOptions setHiddenUnits(List<Long> hiddenUnits)
hiddenUnits
- hiddenUnits or null
for nonepublic String getHolidayRegion()
null
for nonepublic TrainingOptions setHolidayRegion(String holidayRegion)
holidayRegion
- holidayRegion or null
for nonepublic Long getHorizon()
null
for nonepublic TrainingOptions setHorizon(Long horizon)
horizon
- horizon or null
for nonepublic Boolean getIncludeDrift()
null
for nonepublic TrainingOptions setIncludeDrift(Boolean includeDrift)
includeDrift
- includeDrift or null
for nonepublic Double getInitialLearnRate()
null
for nonepublic TrainingOptions setInitialLearnRate(Double initialLearnRate)
initialLearnRate
- initialLearnRate or null
for nonepublic List<String> getInputLabelColumns()
null
for nonepublic TrainingOptions setInputLabelColumns(List<String> inputLabelColumns)
inputLabelColumns
- inputLabelColumns or null
for nonepublic String getItemColumn()
null
for nonepublic TrainingOptions setItemColumn(String itemColumn)
itemColumn
- itemColumn or null
for nonepublic String getKmeansInitializationColumn()
null
for nonepublic TrainingOptions setKmeansInitializationColumn(String kmeansInitializationColumn)
kmeansInitializationColumn
- kmeansInitializationColumn or null
for nonepublic String getKmeansInitializationMethod()
null
for nonepublic TrainingOptions setKmeansInitializationMethod(String kmeansInitializationMethod)
kmeansInitializationMethod
- kmeansInitializationMethod or null
for nonepublic Double getL1Regularization()
null
for nonepublic TrainingOptions setL1Regularization(Double l1Regularization)
l1Regularization
- l1Regularization or null
for nonepublic Double getL2Regularization()
null
for nonepublic TrainingOptions setL2Regularization(Double l2Regularization)
l2Regularization
- l2Regularization or null
for nonepublic Map<String,Double> getLabelClassWeights()
null
for nonepublic TrainingOptions setLabelClassWeights(Map<String,Double> labelClassWeights)
labelClassWeights
- labelClassWeights or null
for nonepublic Double getLearnRate()
null
for nonepublic TrainingOptions setLearnRate(Double learnRate)
learnRate
- learnRate or null
for nonepublic String getLearnRateStrategy()
null
for nonepublic TrainingOptions setLearnRateStrategy(String learnRateStrategy)
learnRateStrategy
- learnRateStrategy or null
for nonepublic String getLossType()
null
for nonepublic TrainingOptions setLossType(String lossType)
lossType
- lossType or null
for nonepublic Long getMaxIterations()
null
for nonepublic TrainingOptions setMaxIterations(Long maxIterations)
maxIterations
- maxIterations or null
for nonepublic Long getMaxTreeDepth()
null
for nonepublic TrainingOptions setMaxTreeDepth(Long maxTreeDepth)
maxTreeDepth
- maxTreeDepth or null
for nonepublic Double getMinRelativeProgress()
null
for nonepublic TrainingOptions setMinRelativeProgress(Double minRelativeProgress)
minRelativeProgress
- minRelativeProgress or null
for nonepublic Double getMinSplitLoss()
null
for nonepublic TrainingOptions setMinSplitLoss(Double minSplitLoss)
minSplitLoss
- minSplitLoss or null
for nonepublic String getModelUri()
null
for nonepublic TrainingOptions setModelUri(String modelUri)
modelUri
- modelUri or null
for nonepublic ArimaOrder getNonSeasonalOrder()
null
for nonepublic TrainingOptions setNonSeasonalOrder(ArimaOrder nonSeasonalOrder)
nonSeasonalOrder
- nonSeasonalOrder or null
for nonepublic Long getNumClusters()
null
for nonepublic TrainingOptions setNumClusters(Long numClusters)
numClusters
- numClusters or null
for nonepublic Long getNumFactors()
null
for nonepublic TrainingOptions setNumFactors(Long numFactors)
numFactors
- numFactors or null
for nonepublic String getOptimizationStrategy()
null
for nonepublic TrainingOptions setOptimizationStrategy(String optimizationStrategy)
optimizationStrategy
- optimizationStrategy or null
for nonepublic Boolean getPreserveInputStructs()
null
for nonepublic TrainingOptions setPreserveInputStructs(Boolean preserveInputStructs)
preserveInputStructs
- preserveInputStructs or null
for nonepublic Double getSubsample()
null
for nonepublic TrainingOptions setSubsample(Double subsample)
subsample
- subsample or null
for nonepublic String getTimeSeriesDataColumn()
null
for nonepublic TrainingOptions setTimeSeriesDataColumn(String timeSeriesDataColumn)
timeSeriesDataColumn
- timeSeriesDataColumn or null
for nonepublic String getTimeSeriesIdColumn()
null
for nonepublic TrainingOptions setTimeSeriesIdColumn(String timeSeriesIdColumn)
timeSeriesIdColumn
- timeSeriesIdColumn or null
for nonepublic String getTimeSeriesTimestampColumn()
null
for nonepublic TrainingOptions setTimeSeriesTimestampColumn(String timeSeriesTimestampColumn)
timeSeriesTimestampColumn
- timeSeriesTimestampColumn or null
for nonepublic String getUserColumn()
null
for nonepublic TrainingOptions setUserColumn(String userColumn)
userColumn
- userColumn or null
for nonepublic Double getWalsAlpha()
null
for nonepublic TrainingOptions setWalsAlpha(Double walsAlpha)
walsAlpha
- walsAlpha or null
for nonepublic Boolean getWarmStart()
null
for nonepublic TrainingOptions setWarmStart(Boolean warmStart)
warmStart
- warmStart or null
for nonepublic TrainingOptions set(String fieldName, Object value)
set
in class GenericJson
public TrainingOptions clone()
clone
in class GenericJson
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