Class TrainingOptions

Options used in model training.

Inheritance

System.Object

TrainingOptions

Implements

Google.Apis.Requests.IDirectResponseSchema

Inherited Members

System.Object.Equals(System.Object)

System.Object.Equals(System.Object, System.Object)

System.Object.GetHashCode()

System.Object.GetType()

System.Object.MemberwiseClone()

System.Object.ReferenceEquals(System.Object, System.Object)

System.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
System.Nullable<System.Boolean>

AutoArima

Whether to enable auto ARIMA or not.

Declaration

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

Property Value

Type	Description
System.Nullable<System.Boolean>

AutoArimaMaxOrder

The max value of non-seasonal p and q.

Declaration

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

Property Value

Type	Description
System.Nullable<System.Int64>

BatchSize

Batch size for dnn models.

Declaration

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

Property Value

Type	Description
System.Nullable<System.Int64>

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
System.Nullable<System.Boolean>

DataFrequency

The data frequency of a time series.

Declaration

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

Property Value

Type	Description
System.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
System.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
System.Nullable<System.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
System.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
System.Nullable<System.Boolean>

DistanceType

Distance type for clustering models.

Declaration

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

Property Value

Type	Description
System.String

Dropout

Dropout probability for dnn models.

Declaration

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

Property Value

Type	Description
System.Nullable<System.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
System.Nullable<System.Boolean>

ETag

The ETag of the item.

Declaration

public virtual string ETag { get; set; }

Property Value

Type	Description
System.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
System.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<System.Nullable<System.Int64>>

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
System.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
System.Nullable<System.Int64>

IncludeDrift

Include drift when fitting an ARIMA model.

Declaration

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

Property Value

Type	Description
System.Nullable<System.Boolean>

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
System.Nullable<System.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<System.String>

ItemColumn

Item column specified for matrix factorization models.

Declaration

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

Property Value

Type	Description
System.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
System.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
System.String

L1Regularization

L1 regularization coefficient.

Declaration

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

Property Value

Type	Description
System.Nullable<System.Double>

L2Regularization

L2 regularization coefficient.

Declaration

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

Property Value

Type	Description
System.Nullable<System.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<System.String, System.Nullable<System.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
System.Nullable<System.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
System.String

LossType

Type of loss function used during training run.

Declaration

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

Property Value

Type	Description
System.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
System.Nullable<System.Int64>

MaxTreeDepth

Maximum depth of a tree for boosted tree models.

Declaration

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

Property Value

Type	Description
System.Nullable<System.Int64>

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
System.Nullable<System.Double>

MinSplitLoss

Minimum split loss for boosted tree models.

Declaration

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

Property Value

Type	Description
System.Nullable<System.Double>

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
System.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
System.Nullable<System.Int64>

NumFactors

Num factors specified for matrix factorization models.

Declaration

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

Property Value

Type	Description
System.Nullable<System.Int64>

OptimizationStrategy

Optimization strategy for training linear regression models.

Declaration

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

Property Value

Type	Description
System.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
System.Nullable<System.Boolean>

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
System.Nullable<System.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
System.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
System.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<System.String>

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
System.String

UserColumn

User column specified for matrix factorization models.

Declaration

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

Property Value

Type	Description
System.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
System.Nullable<System.Double>

WarmStart

Whether to train a model from the last checkpoint.

Declaration

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

Property Value

Type	Description
System.Nullable<System.Boolean>

Implements

Google.Apis.Requests.IDirectResponseSchema