Class GlobalContrastScaler<T>

Namespace

AiDotNet.Preprocessing.Scalers

Assembly

AiDotNet.dll

Scales features by adjusting contrast based on mean and standard deviation.

public class GlobalContrastScaler<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>>

GlobalContrastScaler<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

Global contrast scaling transforms data using the formula: (x - mean) / (2 * stdDev) + 0.5 This centers values around 0.5 and typically results in values between 0 and 1.

For Beginners: This scaler improves the "contrast" of your data: - It centers values around 0.5 (the new average) - Values above average become > 0.5, below average become < 0.5 - Most values end up between 0 and 1

Example: [68, 70, 71, 69, 72] → [0.3, 0.5, 0.6, 0.4, 0.7] Now the differences between values are more visible.

Constructors

GlobalContrastScaler(int[]?)

Creates a new instance of GlobalContrastScaler<T>.

public GlobalContrastScaler(int[]? columnIndices = null)

Parameters

columnIndices int[]

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

Properties

Mean

Gets the mean for each feature computed during fitting.

public Vector<T>? Mean { get; }

Property Value

Vector<T>

StdDev

Gets the standard deviation for each feature computed during fitting.

public Vector<T>? StdDev { get; }

Property Value

Vector<T>

SupportsInverseTransform

Gets whether this transformer supports inverse transformation.

public override bool SupportsInverseTransform { get; }

Property Value

bool

Methods

FitCore(Matrix<T>)

Computes the mean and standard deviation for each feature from the training data.

protected override void FitCore(Matrix<T> data)

Parameters

data Matrix<T>

The training data matrix where each column is a feature.

GetFeatureNamesOut(string[]?)

Gets the output feature names after transformation.

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

Parameters

inputFeatureNames string[]

The input feature names.

Returns

string[]

The same feature names (GlobalContrastScaler doesn't change number of features).

InverseTransformCore(Matrix<T>)

Reverses the global contrast scaling transformation.

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

Parameters

data Matrix<T>

The scaled data.

Returns

Matrix<T>

The original-scale data.

TransformCore(Matrix<T>)

Transforms the data by applying global contrast scaling.

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

Parameters

data Matrix<T>

The data to transform.

Returns

Matrix<T>

The scaled data with values typically between 0 and 1.