Class LSTMVAEOptions<T>

Namespace

AiDotNet.TimeSeries.AnomalyDetection

Assembly

AiDotNet.dll

Options for LSTM-VAE model.

public class LSTMVAEOptions<T> : TimeSeriesRegressionOptions<T>

Type Parameters

T

Inheritance

object

ModelOptions

RegressionOptions<T>

TimeSeriesRegressionOptions<T>

LSTMVAEOptions<T>

Inherited Members

TimeSeriesRegressionOptions<T>.LagOrder

TimeSeriesRegressionOptions<T>.IncludeTrend

TimeSeriesRegressionOptions<T>.SeasonalPeriod

TimeSeriesRegressionOptions<T>.AutocorrelationCorrection

TimeSeriesRegressionOptions<T>.ModelType

TimeSeriesRegressionOptions<T>.LossFunction

RegressionOptions<T>.DecompositionMethod

RegressionOptions<T>.UseIntercept

ModelOptions.Seed

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Constructors

LSTMVAEOptions()

public LSTMVAEOptions()

LSTMVAEOptions(LSTMVAEOptions<T>)

public LSTMVAEOptions(LSTMVAEOptions<T> other)

Parameters

other LSTMVAEOptions<T>

Properties

BatchSize

public int BatchSize { get; set; }

Property Value

int

Epochs

public int Epochs { get; set; }

Property Value

int

HiddenSize

public int HiddenSize { get; set; }

Property Value

int

KLWeight

Weight for KL divergence term in the loss function (beta in β-VAE). Higher values encourage more regularized latent space.

public double KLWeight { get; set; }

Property Value

double

LatentDim

public int LatentDim { get; set; }

Property Value

int

LearningRate

public double LearningRate { get; set; }

Property Value

double

WindowSize

public int WindowSize { get; set; }

Property Value

int