Class IQRClipper<T>

Namespace

AiDotNet.Preprocessing.OutlierHandling

Assembly

AiDotNet.dll

Clips outliers using the Interquartile Range (IQR) method.

public class IQRClipper<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>>

IQRClipper<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

IQRClipper identifies outliers using the IQR method: - Lower bound = Q1 - k * IQR - Upper bound = Q3 + k * IQR where IQR = Q3 - Q1 and k is the multiplier (default 1.5).

This is the same method used in box plots for identifying outliers. A multiplier of 1.5 identifies "mild" outliers, while 3.0 identifies "extreme" outliers.

For Beginners: The IQR is the range where the middle 50% of data falls. Values outside 1.5× this range are considered outliers: - Q1 (25th percentile): 25% of data is below this value - Q3 (75th percentile): 75% of data is below this value - IQR = Q3 - Q1: The spread of the middle 50% - Outliers: Values below Q1 - 1.5×IQR or above Q3 + 1.5×IQR

Constructors

IQRClipper(double, int[]?)

Creates a new instance of IQRClipper<T>.

public IQRClipper(double multiplier = 1.5, int[]? columnIndices = null)

Parameters

multiplier double

The IQR multiplier (default 1.5 for mild outliers, 3.0 for extreme).

columnIndices int[]

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

Properties

IQRValues

Gets the IQR values for each feature.

public double[]? IQRValues { get; }

Property Value

double[]

LowerBounds

Gets the fitted lower bounds for each feature.

public double[]? LowerBounds { get; }

Property Value

double[]

Multiplier

Gets the IQR multiplier for determining outlier boundaries.

public double Multiplier { get; }

Property Value

double

Q1Values

Gets the Q1 (25th percentile) values for each feature.

public double[]? Q1Values { get; }

Property Value

double[]

Q3Values

Gets the Q3 (75th percentile) values for each feature.

public double[]? Q3Values { get; }

Property Value

double[]

SupportsInverseTransform

Gets whether this transformer supports inverse transformation.

public override bool SupportsInverseTransform { get; }

Property Value

bool

UpperBounds

Gets the fitted upper bounds for each feature.

public double[]? UpperBounds { get; }

Property Value

double[]

Methods

CountOutliersPerFeature(Matrix<T>)

Counts the number of outliers per feature.

public int[] CountOutliersPerFeature(Matrix<T> data)

Parameters

data Matrix<T>

The data to analyze.

Returns

int[]

Array of outlier counts per feature.

FitCore(Matrix<T>)

Fits the clipper by computing IQR bounds for 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[]

GetOutlierMask(Matrix<T>)

Gets a mask indicating which values are outliers in the input data.

public bool[,] GetOutlierMask(Matrix<T> data)

Parameters

data Matrix<T>

The data to check for outliers.

Returns

bool[,]

A boolean matrix where true indicates an outlier.

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 clipping values outside IQR bounds.

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

Parameters

data Matrix<T>

The data to transform.

Returns

Matrix<T>

The transformed data with outliers clipped.