Class VarianceThreshold<T>

Namespace

AiDotNet.Preprocessing.FeatureSelection

Assembly

AiDotNet.dll

Feature selector that removes features with variance below a threshold.

public class VarianceThreshold<T> : TransformerBase<T, Matrix<T>, Matrix<T>>, IDataTransformer<T, Matrix<T>, Matrix<T>>

Type Parameters

T

The numeric type for calculations (e.g., float, double).

Inheritance

object

TransformerBase<T, Matrix<T>, Matrix<T>>

VarianceThreshold<T>

Implements

IDataTransformer<T, Matrix<T>, Matrix<T>>

Inherited Members

TransformerBase<T, Matrix<T>, Matrix<T>>.NumOps

TransformerBase<T, Matrix<T>, Matrix<T>>.Engine

TransformerBase<T, Matrix<T>, Matrix<T>>.IsFitted

TransformerBase<T, Matrix<T>, Matrix<T>>.ColumnIndices

TransformerBase<T, Matrix<T>, Matrix<T>>.SupportsInverseTransform

TransformerBase<T, Matrix<T>, Matrix<T>>.Fit(Matrix<T>)

TransformerBase<T, Matrix<T>, Matrix<T>>.Transform(Matrix<T>)

TransformerBase<T, Matrix<T>, Matrix<T>>.FitTransform(Matrix<T>)

TransformerBase<T, Matrix<T>, Matrix<T>>.InverseTransform(Matrix<T>)

TransformerBase<T, Matrix<T>, Matrix<T>>.GetFeatureNamesOut(string[])

TransformerBase<T, Matrix<T>, Matrix<T>>.FitCore(Matrix<T>)

TransformerBase<T, Matrix<T>, Matrix<T>>.TransformCore(Matrix<T>)

TransformerBase<T, Matrix<T>, Matrix<T>>.InverseTransformCore(Matrix<T>)

TransformerBase<T, Matrix<T>, Matrix<T>>.ValidateInputData(Matrix<T>)

TransformerBase<T, Matrix<T>, Matrix<T>>.EnsureFitted()

TransformerBase<T, Matrix<T>, Matrix<T>>.GetColumnsToProcess(int)

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Remarks

VarianceThreshold removes all features whose variance doesn't meet a minimum threshold. Features with low variance are often not informative because they don't vary enough across samples to be useful for prediction.

For Beginners: If a feature has the same value (or nearly the same value) for all samples, it won't help your model distinguish between different outcomes. This transformer automatically removes such features: - Constant features (all same value) have variance = 0 - Near-constant features have very low variance

Example: A "Country" column that is "USA" for 99.9% of rows provides little information.

Constructors

VarianceThreshold(double, int[]?)

Creates a new instance of VarianceThreshold<T>.

public VarianceThreshold(double threshold = 0, int[]? columnIndices = null)

Parameters

threshold double

Features with variance below this are removed. Defaults to 0.0.

columnIndices int[]

The column indices to consider, or null for all columns.

Properties

SelectedFeatures

Gets the indices of selected features.

public int[]? SelectedFeatures { get; }

Property Value

int[]

SupportsInverseTransform

Gets whether this transformer supports inverse transformation.

public override bool SupportsInverseTransform { get; }

Property Value

bool

Threshold

Gets the variance threshold.

public double Threshold { get; }

Property Value

double

Variances

Gets the computed variances for each feature.

public double[]? Variances { get; }

Property Value

double[]

Methods

FitCore(Matrix<T>)

Computes the variance of each feature.

protected override void FitCore(Matrix<T> data)

Parameters

data Matrix<T>

The training data matrix.

GetFeatureNamesOut(string[]?)

Gets the output feature names after transformation.

public override string[] GetFeatureNamesOut(string[]? inputFeatureNames = null)

Parameters

inputFeatureNames string[]

Returns

string[]

GetSupportMask()

Gets a boolean mask indicating which features are selected.

public bool[] GetSupportMask()

Returns

bool[]

Array where true indicates the feature is selected.

InverseTransformCore(Matrix<T>)

Inverse transformation is not supported.

protected override Matrix<T> InverseTransformCore(Matrix<T> data)

Parameters

data Matrix<T>

Returns

Matrix<T>

TransformCore(Matrix<T>)

Removes features with variance below the threshold.

protected override Matrix<T> TransformCore(Matrix<T> data)

Parameters

data Matrix<T>

The data to transform.

Returns

Matrix<T>

The data with low-variance features removed.