Class QuantileTransformer<T>

Namespace

AiDotNet.Preprocessing.PowerTransforms

Assembly

AiDotNet.dll

Transforms features to follow a uniform or normal distribution using quantile information.

public class QuantileTransformer<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>>

QuantileTransformer<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

QuantileTransformer applies a non-linear transformation that maps the input distribution to either a uniform or normal (Gaussian) distribution. This is effective at reducing the impact of outliers and normalizing non-Gaussian distributions.

For Beginners: This transformer redistributes your data to match a desired pattern: - Uniform: Spreads values evenly across [0, 1] - Normal: Creates a bell curve distribution

Example with uniform output: [1, 1, 2, 3, 5, 8, 13, 100, 1000] → [0.0, 0.125, 0.25, 0.375, 0.5, 0.625, 0.75, 0.875, 1.0] Notice how extreme values (100, 1000) no longer dominate.

Constructors

QuantileTransformer(OutputDistributionType, int, int[]?)

Creates a new instance of QuantileTransformer<T>.

public QuantileTransformer(OutputDistributionType outputDistribution = OutputDistributionType.Uniform, int nQuantiles = 1000, int[]? columnIndices = null)

Parameters

outputDistribution OutputDistributionType

The target distribution. Defaults to Uniform.

nQuantiles int

The number of quantiles to compute. Defaults to 1000.

columnIndices int[]

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

Properties

NQuantiles

Gets the number of quantiles used.

public int NQuantiles { get; }

Property Value

int

OutputDistribution

Gets the target output distribution.

public OutputDistributionType OutputDistribution { get; }

Property Value

OutputDistributionType

Quantiles

Gets the quantiles for each feature computed during fitting.

public List<T[]>? Quantiles { get; }

Property Value

List<T[]>

SupportsInverseTransform

Gets whether this transformer supports inverse transformation.

public override bool SupportsInverseTransform { get; }

Property Value

bool

Methods

FitCore(Matrix<T>)

Computes the quantiles 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 (QuantileTransformer doesn't change number of features).

InverseTransformCore(Matrix<T>)

Reverses the quantile transformation.

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

Parameters

data Matrix<T>

The transformed data.

Returns

Matrix<T>

The original-scale data.

TransformCore(Matrix<T>)

Transforms the data by mapping to the target distribution.

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

Parameters

data Matrix<T>

The data to transform.

Returns

Matrix<T>

The transformed data following the target distribution.