Class TrainingOptions

Options used in model training.

Inheritance

object

TrainingOptions

Implements

IDirectResponseSchema

Inherited Members

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Namespace: Google.Apis.Bigquery.v2.Data

Assembly: Google.Apis.Bigquery.v2.dll

Syntax

public class TrainingOptions : IDirectResponseSchema

Properties

AdjustStepChanges

If true, detect step changes and make data adjustment in the input time series.

Declaration

[JsonProperty("adjustStepChanges")]
public virtual bool? AdjustStepChanges { get; set; }

Property Value

Type	Description
bool?

AutoArima

Whether to enable auto ARIMA or not.

Declaration

[JsonProperty("autoArima")]
public virtual bool? AutoArima { get; set; }

Property Value

Type	Description
bool?

AutoArimaMaxOrder

The max value of non-seasonal p and q.

Declaration

[JsonProperty("autoArimaMaxOrder")]
public virtual long? AutoArimaMaxOrder { get; set; }

Property Value

Type	Description
long?

BatchSize

Batch size for dnn models.

Declaration

[JsonProperty("batchSize")]
public virtual long? BatchSize { get; set; }

Property Value

Type	Description
long?

BoosterType

Booster type for boosted tree models.

Declaration

[JsonProperty("boosterType")]
public virtual string BoosterType { get; set; }

Property Value

Type	Description
string

CalculatePValues

Whether or not p-value test should be computed for this model. Only available for linear and logistic regression models.

Declaration

[JsonProperty("calculatePValues")]
public virtual bool? CalculatePValues { get; set; }

Property Value

Type	Description
bool?

CleanSpikesAndDips

If true, clean spikes and dips in the input time series.

Declaration

[JsonProperty("cleanSpikesAndDips")]
public virtual bool? CleanSpikesAndDips { get; set; }

Property Value

Type	Description
bool?

ColorSpace

Enums for color space, used for processing images in Object Table. See more details at https://www.tensorflow.org/io/tutorials/colorspace.

Declaration

[JsonProperty("colorSpace")]
public virtual string ColorSpace { get; set; }

Property Value

Type	Description
string

ColsampleBylevel

Subsample ratio of columns for each level for boosted tree models.

Declaration

[JsonProperty("colsampleBylevel")]
public virtual double? ColsampleBylevel { get; set; }

Property Value

Type	Description
double?

ColsampleBynode

Subsample ratio of columns for each node(split) for boosted tree models.

Declaration

[JsonProperty("colsampleBynode")]
public virtual double? ColsampleBynode { get; set; }

Property Value

Type	Description
double?

ColsampleBytree

Subsample ratio of columns when constructing each tree for boosted tree models.

Declaration

[JsonProperty("colsampleBytree")]
public virtual double? ColsampleBytree { get; set; }

Property Value

Type	Description
double?

DartNormalizeType

Type of normalization algorithm for boosted tree models using dart booster.

Declaration

[JsonProperty("dartNormalizeType")]
public virtual string DartNormalizeType { get; set; }

Property Value

Type	Description
string

DataFrequency

The data frequency of a time series.

Declaration

[JsonProperty("dataFrequency")]
public virtual string DataFrequency { get; set; }

Property Value

Type	Description
string

DataSplitColumn

The column to split data with. This column won't be used as a feature. 1. When data_split_method is CUSTOM, the corresponding column should be boolean. The rows with true value tag are eval data, and the false are training data. 2. When data_split_method is SEQ, the first DATA_SPLIT_EVAL_FRACTION rows (from smallest to largest) in the corresponding column are used as training data, and the rest are eval data. It respects the order in Orderable data types: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#data-type-properties

Declaration

[JsonProperty("dataSplitColumn")]
public virtual string DataSplitColumn { get; set; }

Property Value

Type	Description
string

DataSplitEvalFraction

The fraction of evaluation data over the whole input data. The rest of data will be used as training data. The format should be double. Accurate to two decimal places. Default value is 0.2.

Declaration

[JsonProperty("dataSplitEvalFraction")]
public virtual double? DataSplitEvalFraction { get; set; }

Property Value

Type	Description
double?

DataSplitMethod

The data split type for training and evaluation, e.g. RANDOM.

Declaration

[JsonProperty("dataSplitMethod")]
public virtual string DataSplitMethod { get; set; }

Property Value

Type	Description
string

DecomposeTimeSeries

If true, perform decompose time series and save the results.

Declaration

[JsonProperty("decomposeTimeSeries")]
public virtual bool? DecomposeTimeSeries { get; set; }

Property Value

Type	Description
bool?

DistanceType

Distance type for clustering models.

Declaration

[JsonProperty("distanceType")]
public virtual string DistanceType { get; set; }

Property Value

Type	Description
string

Dropout

Dropout probability for dnn models.

Declaration

[JsonProperty("dropout")]
public virtual double? Dropout { get; set; }

Property Value

Type	Description
double?

EarlyStop

Whether to stop early when the loss doesn't improve significantly any more (compared to min_relative_progress). Used only for iterative training algorithms.

Declaration

[JsonProperty("earlyStop")]
public virtual bool? EarlyStop { get; set; }

Property Value

Type	Description
bool?

EnableGlobalExplain

If true, enable global explanation during training.

Declaration

[JsonProperty("enableGlobalExplain")]
public virtual bool? EnableGlobalExplain { get; set; }

Property Value

Type	Description
bool?

ETag

The ETag of the item.

Declaration

public virtual string ETag { get; set; }

Property Value

Type	Description
string

FeedbackType

Feedback type that specifies which algorithm to run for matrix factorization.

Declaration

[JsonProperty("feedbackType")]
public virtual string FeedbackType { get; set; }

Property Value

Type	Description
string

HiddenUnits

Hidden units for dnn models.

Declaration

[JsonProperty("hiddenUnits")]
public virtual IList<long?> HiddenUnits { get; set; }

Property Value

Type	Description
System.Collections.Generic.IList<T><long?>

HolidayRegion

The geographical region based on which the holidays are considered in time series modeling. If a valid value is specified, then holiday effects modeling is enabled.

Declaration

[JsonProperty("holidayRegion")]
public virtual string HolidayRegion { get; set; }

Property Value

Type	Description
string

Horizon

The number of periods ahead that need to be forecasted.

Declaration

[JsonProperty("horizon")]
public virtual long? Horizon { get; set; }

Property Value

Type	Description
long?

HparamTuningObjectives

The target evaluation metrics to optimize the hyperparameters for.

Declaration

[JsonProperty("hparamTuningObjectives")]
public virtual IList<string> HparamTuningObjectives { get; set; }

Property Value

Type	Description
System.Collections.Generic.IList<T><string>

IncludeDrift

Include drift when fitting an ARIMA model.

Declaration

[JsonProperty("includeDrift")]
public virtual bool? IncludeDrift { get; set; }

Property Value

Type	Description
bool?

InitialLearnRate

Specifies the initial learning rate for the line search learn rate strategy.

Declaration

[JsonProperty("initialLearnRate")]
public virtual double? InitialLearnRate { get; set; }

Property Value

Type	Description
double?

InputLabelColumns

Name of input label columns in training data.

Declaration

[JsonProperty("inputLabelColumns")]
public virtual IList<string> InputLabelColumns { get; set; }

Property Value

Type	Description
System.Collections.Generic.IList<T><string>

IntegratedGradientsNumSteps

Number of integral steps for the integrated gradients explain method.

Declaration

[JsonProperty("integratedGradientsNumSteps")]
public virtual long? IntegratedGradientsNumSteps { get; set; }

Property Value

Type	Description
long?

ItemColumn

Item column specified for matrix factorization models.

Declaration

[JsonProperty("itemColumn")]
public virtual string ItemColumn { get; set; }

Property Value

Type	Description
string

KmeansInitializationColumn

The column used to provide the initial centroids for kmeans algorithm when kmeans_initialization_method is CUSTOM.

Declaration

[JsonProperty("kmeansInitializationColumn")]
public virtual string KmeansInitializationColumn { get; set; }

Property Value

Type	Description
string

KmeansInitializationMethod

The method used to initialize the centroids for kmeans algorithm.

Declaration

[JsonProperty("kmeansInitializationMethod")]
public virtual string KmeansInitializationMethod { get; set; }

Property Value

Type	Description
string

L1Regularization

L1 regularization coefficient.

Declaration

[JsonProperty("l1Regularization")]
public virtual double? L1Regularization { get; set; }

Property Value

Type	Description
double?

L2Regularization

L2 regularization coefficient.

Declaration

[JsonProperty("l2Regularization")]
public virtual double? L2Regularization { get; set; }

Property Value

Type	Description
double?

LabelClassWeights

Weights associated with each label class, for rebalancing the training data. Only applicable for classification models.

Declaration

[JsonProperty("labelClassWeights")]
public virtual IDictionary<string, double?> LabelClassWeights { get; set; }

Property Value

Type	Description
System.Collections.Generic.IDictionary<TKey, TValue><string, double?>

LearnRate

Learning rate in training. Used only for iterative training algorithms.

Declaration

[JsonProperty("learnRate")]
public virtual double? LearnRate { get; set; }

Property Value

Type	Description
double?

LearnRateStrategy

The strategy to determine learn rate for the current iteration.

Declaration

[JsonProperty("learnRateStrategy")]
public virtual string LearnRateStrategy { get; set; }

Property Value

Type	Description
string

LossType

Type of loss function used during training run.

Declaration

[JsonProperty("lossType")]
public virtual string LossType { get; set; }

Property Value

Type	Description
string

MaxIterations

The maximum number of iterations in training. Used only for iterative training algorithms.

Declaration

[JsonProperty("maxIterations")]
public virtual long? MaxIterations { get; set; }

Property Value

Type	Description
long?

MaxParallelTrials

Maximum number of trials to run in parallel.

Declaration

[JsonProperty("maxParallelTrials")]
public virtual long? MaxParallelTrials { get; set; }

Property Value

Type	Description
long?

MaxTimeSeriesLength

Get truncated length by last n points in time series. Use separately from time_series_length_fraction and min_time_series_length.

Declaration

[JsonProperty("maxTimeSeriesLength")]
public virtual long? MaxTimeSeriesLength { get; set; }

Property Value

Type	Description
long?

MaxTreeDepth

Maximum depth of a tree for boosted tree models.

Declaration

[JsonProperty("maxTreeDepth")]
public virtual long? MaxTreeDepth { get; set; }

Property Value

Type	Description
long?

MinRelativeProgress

When early_stop is true, stops training when accuracy improvement is less than 'min_relative_progress'. Used only for iterative training algorithms.

Declaration

[JsonProperty("minRelativeProgress")]
public virtual double? MinRelativeProgress { get; set; }

Property Value

Type	Description
double?

MinSplitLoss

Minimum split loss for boosted tree models.

Declaration

[JsonProperty("minSplitLoss")]
public virtual double? MinSplitLoss { get; set; }

Property Value

Type	Description
double?

MinTimeSeriesLength

Set fast trend ARIMA_PLUS model minimum training length. Use in pair with time_series_length_fraction.

Declaration

[JsonProperty("minTimeSeriesLength")]
public virtual long? MinTimeSeriesLength { get; set; }

Property Value

Type	Description
long?

MinTreeChildWeight

Minimum sum of instance weight needed in a child for boosted tree models.

Declaration

[JsonProperty("minTreeChildWeight")]
public virtual long? MinTreeChildWeight { get; set; }

Property Value

Type	Description
long?

ModelUri

Google Cloud Storage URI from which the model was imported. Only applicable for imported models.

Declaration

[JsonProperty("modelUri")]
public virtual string ModelUri { get; set; }

Property Value

Type	Description
string

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.

Declaration

[JsonProperty("nonSeasonalOrder")]
public virtual ArimaOrder NonSeasonalOrder { get; set; }

Property Value

Type	Description
ArimaOrder

NumClusters

Number of clusters for clustering models.

Declaration

[JsonProperty("numClusters")]
public virtual long? NumClusters { get; set; }

Property Value

Type	Description
long?

NumFactors

Num factors specified for matrix factorization models.

Declaration

[JsonProperty("numFactors")]
public virtual long? NumFactors { get; set; }

Property Value

Type	Description
long?

NumParallelTree

Number of parallel trees constructed during each iteration for boosted tree models.

Declaration

[JsonProperty("numParallelTree")]
public virtual long? NumParallelTree { get; set; }

Property Value

Type	Description
long?

NumTrials

Number of trials to run this hyperparameter tuning job.

Declaration

[JsonProperty("numTrials")]
public virtual long? NumTrials { get; set; }

Property Value

Type	Description
long?

OptimizationStrategy

Optimization strategy for training linear regression models.

Declaration

[JsonProperty("optimizationStrategy")]
public virtual string OptimizationStrategy { get; set; }

Property Value

Type	Description
string

PreserveInputStructs

Whether to preserve the input structs in output feature names. Suppose there is a struct A with field b. When false (default), the output feature name is A_b. When true, the output feature name is A.b.

Declaration

[JsonProperty("preserveInputStructs")]
public virtual bool? PreserveInputStructs { get; set; }

Property Value

Type	Description
bool?

SampledShapleyNumPaths

Number of paths for the sampled Shapley explain method.

Declaration

[JsonProperty("sampledShapleyNumPaths")]
public virtual long? SampledShapleyNumPaths { get; set; }

Property Value

Type	Description
long?

Subsample

Subsample fraction of the training data to grow tree to prevent overfitting for boosted tree models.

Declaration

[JsonProperty("subsample")]
public virtual double? Subsample { get; set; }

Property Value

Type	Description
double?

TimeSeriesDataColumn

Column to be designated as time series data for ARIMA model.

Declaration

[JsonProperty("timeSeriesDataColumn")]
public virtual string TimeSeriesDataColumn { get; set; }

Property Value

Type	Description
string

TimeSeriesIdColumn

The time series id column that was used during ARIMA model training.

Declaration

[JsonProperty("timeSeriesIdColumn")]
public virtual string TimeSeriesIdColumn { get; set; }

Property Value

Type	Description
string

TimeSeriesIdColumns

The time series id columns that were used during ARIMA model training.

Declaration

[JsonProperty("timeSeriesIdColumns")]
public virtual IList<string> TimeSeriesIdColumns { get; set; }

Property Value

Type	Description
System.Collections.Generic.IList<T><string>

TimeSeriesLengthFraction

Get truncated length by fraction in time series.

Declaration

[JsonProperty("timeSeriesLengthFraction")]
public virtual double? TimeSeriesLengthFraction { get; set; }

Property Value

Type	Description
double?

TimeSeriesTimestampColumn

Column to be designated as time series timestamp for ARIMA model.

Declaration

[JsonProperty("timeSeriesTimestampColumn")]
public virtual string TimeSeriesTimestampColumn { get; set; }

Property Value

Type	Description
string

TreeMethod

Tree construction algorithm for boosted tree models.

Declaration

[JsonProperty("treeMethod")]
public virtual string TreeMethod { get; set; }

Property Value

Type	Description
string

TrendSmoothingWindowSize

The smoothing window size for the trend component of the time series.

Declaration

[JsonProperty("trendSmoothingWindowSize")]
public virtual long? TrendSmoothingWindowSize { get; set; }

Property Value

Type	Description
long?

UserColumn

User column specified for matrix factorization models.

Declaration

[JsonProperty("userColumn")]
public virtual string UserColumn { get; set; }

Property Value

Type	Description
string

WalsAlpha

Hyperparameter for matrix factoration when implicit feedback type is specified.

Declaration

[JsonProperty("walsAlpha")]
public virtual double? WalsAlpha { get; set; }

Property Value

Type	Description
double?

WarmStart

Whether to train a model from the last checkpoint.

Declaration

[JsonProperty("warmStart")]
public virtual bool? WarmStart { get; set; }

Property Value

Type	Description
bool?

Implements

IDirectResponseSchema