Class SelectFdr<T>

Namespace

AiDotNet.Preprocessing.FeatureSelection

Assembly

AiDotNet.dll

Selects features based on a false discovery rate test.

public class SelectFdr<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>>

SelectFdr<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

SelectFdr applies the Benjamini-Hochberg procedure to control the expected proportion of false discoveries (incorrectly selected features) among the selected features.

Unlike SelectFpr which controls false positives among ALL features, SelectFdr controls false discoveries among SELECTED features only.

For Beginners: FDR correction is more powerful than FPR: - FPR: "At most 5% of all 1000 features are false positives" - FDR: "At most 5% of the 50 features I selected are false positives" - FDR allows more features to be selected while controlling errors

Constructors

SelectFdr(double, SelectKBestScoreFunc, int[]?)

Creates a new instance of SelectFdr<T>.

public SelectFdr(double alpha = 0.05, SelectKBestScoreFunc scoringFunction = SelectKBestScoreFunc.FRegression, int[]? columnIndices = null)

Parameters

alpha double

Target FDR level. Defaults to 0.05.

scoringFunction SelectKBestScoreFunc

The scoring function to use. Defaults to FRegression.

columnIndices int[]

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

Properties

AdjustedPValues

Gets the FDR-adjusted p-values.

public double[]? AdjustedPValues { get; }

Property Value

double[]

Alpha

Gets the significance level (alpha) for FDR control.

public double Alpha { get; }

Property Value

double

PValues

Gets the original p-values for each feature.

public double[]? PValues { get; }

Property Value

double[]

Scores

Gets the scores for each feature.

public double[]? Scores { get; }

Property Value

double[]

ScoringFunction

Gets the scoring function used.

public SelectKBestScoreFunc ScoringFunction { get; }

Property Value

SelectKBestScoreFunc

SelectedIndices

Gets the indices of selected features.

public int[]? SelectedIndices { get; }

Property Value

int[]

SupportsInverseTransform

Gets whether this transformer supports inverse transformation.

public override bool SupportsInverseTransform { get; }

Property Value

bool

Methods

Fit(Matrix<T>, Vector<T>)

Fits the selector by computing FDR-adjusted p-values.

public void Fit(Matrix<T> data, Vector<T> target)

Parameters

data Matrix<T>

The feature matrix.

target Vector<T>

The target values.

FitCore(Matrix<T>)

Fits the selector (requires target via specialized Fit method).

protected override void FitCore(Matrix<T> data)

Parameters

data Matrix<T>

FitTransform(Matrix<T>, Vector<T>)

Fits and transforms the data.

public Matrix<T> FitTransform(Matrix<T> data, Vector<T> target)

Parameters

data Matrix<T>

target Vector<T>

Returns

Matrix<T>

GetFeatureNamesOut(string[]?)

Gets the output feature names after transformation.

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

Parameters

inputFeatureNames string[]

Returns

string[]

GetSupportMask()

Gets the support mask indicating which features are selected.

public bool[] GetSupportMask()

Returns

bool[]

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>)

Transforms the data by selecting features passing FDR threshold.

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

Parameters

data Matrix<T>

Returns

Matrix<T>