Class MEstimateEncoder<T>

Namespace

AiDotNet.Preprocessing.Encoders

Assembly

AiDotNet.dll

Encodes categorical features using M-estimate regularization.

public class MEstimateEncoder<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>>

MEstimateEncoder<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

MEstimateEncoder applies M-estimate smoothing to target encoding, which adds a regularization parameter 'm' that controls shrinkage toward the global mean.

The formula: encoded = (n * category_mean + m * global_mean) / (n + m) where n is the count of samples in the category and m is the smoothing parameter.

For Beginners: M-estimate is like adding 'm' fake samples: - Each fake sample has the global mean as its target - Categories with few samples get pulled toward the global mean - Categories with many samples stay close to their actual mean - Higher m = more smoothing toward global mean

Constructors

MEstimateEncoder(double, MEstimateHandleUnknown, int[]?)

Creates a new instance of MEstimateEncoder<T>.

public MEstimateEncoder(double m = 1, MEstimateHandleUnknown handleUnknown = MEstimateHandleUnknown.UseGlobalMean, int[]? columnIndices = null)

Parameters

m double

Smoothing parameter (number of virtual samples). Defaults to 1.0.

handleUnknown MEstimateHandleUnknown

How to handle unknown categories. Defaults to UseGlobalMean.

columnIndices int[]

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

Properties

GlobalMean

Gets the global target mean.

public double GlobalMean { get; }

Property Value

double

HandleUnknown

Gets how unknown categories are handled.

public MEstimateHandleUnknown HandleUnknown { get; }

Property Value

MEstimateHandleUnknown

M

Gets the smoothing parameter m.

public double M { get; }

Property Value

double

SupportsInverseTransform

Gets whether this transformer supports inverse transformation.

public override bool SupportsInverseTransform { get; }

Property Value

bool

Methods

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

Fits the encoder by computing M-estimate encodings.

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

Parameters

data Matrix<T>

The feature matrix to fit.

target Vector<T>

The target values.

FitCore(Matrix<T>)

Fits the encoder (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[]

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 using fitted encodings.

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

Parameters

data Matrix<T>

Returns

Matrix<T>