Uses of Interface
elki.math.linearalgebra.pca.weightfunctions.WeightFunction

Packages that use WeightFunction

Package	Description
elki.math.linearalgebra.pca	Principal Component Analysis (PCA) and eigenvector processing.
elki.math.linearalgebra.pca.weightfunctions	Weight functions used in weighted PCA via WeightedCovarianceMatrixBuilder.

Uses of WeightFunction in elki.math.linearalgebra.pca

Fields in elki.math.linearalgebra.pca declared as WeightFunction

Modifier and Type	Field	Description
protected WeightFunction	WeightedCovarianceMatrixBuilder.Par.weightfunction	Weight function.
protected WeightFunction	WeightedCovarianceMatrixBuilder.weightfunction	Holds the weight function.

Constructors in elki.math.linearalgebra.pca with parameters of type WeightFunction

Constructor	Description
WeightedCovarianceMatrixBuilder(WeightFunction weightfunction)	Constructor.

Uses of WeightFunction in elki.math.linearalgebra.pca.weightfunctions

Classes in elki.math.linearalgebra.pca.weightfunctions that implement WeightFunction

Modifier and Type	Class	Description
class	ConstantWeight	Constant weight function.
class	ErfcStddevWeight	Gaussian Error Function Weight function, scaled using stddev using: \( \text{erfc}(\frac{1}{\sqrt{2}} \frac{\text{distance}}{\sigma}) \).
class	ErfcWeight	Gaussian Error Function Weight function, scaled such that the result it 0.1 when the distance is the maximum using: \( \text{erfc}(1.1630871536766736 \frac{\text{distance}}{\max}) \).
class	ExponentialStddevWeight	Exponential Weight function, scaled using the standard deviation using: \( \sigma \exp(-\frac{1}{2} \frac{\text{distance}}{\sigma}) \).
class	ExponentialWeight	Exponential Weight function, scaled such that the result it 0.1 at distance equal max, so it does not completely disappear using: \( \exp(-2.3025850929940455 \frac{\text{distance}}{\max}) \)
class	GaussStddevWeight	Gaussian weight function, scaled using standard deviation \( \frac{1}{\sqrt{2\pi}} \exp(-\frac{\text{dist}^2}{2\sigma^2}) \)
class	GaussWeight	Gaussian weight function, scaled such that the result it 0.1 when distance equals the maximum, using \( \exp(-2.3025850929940455 \frac{\text{dist}^2}{\max^2}) \).
class	InverseLinearWeight	Inverse linear weight function using \(.1+0.9\frac{\text{distance}}{\max}\).
class	InverseProportionalStddevWeight	Inverse proportional weight function, scaled using the standard deviation using: \( 1 / (1 + \frac{distance}{\sigma}) \)
class	InverseProportionalWeight	Inverse proportional weight function, scaled using the maximum using: \( 1 / (1 + \frac{\text{distance}}{\max} ) \)
class	LinearWeight	Linear weight function, scaled using the maximum such that it goes from 1.0 to 0.1 using: \( 1 - 0.9 \frac{\text{distance}}{\max} \)
class	QuadraticStddevWeight	Quadratic weight function, scaled using the standard deviation: \( \max\{0.0, 1.0 - \frac{\text{dist}^2}{3\sigma^2} \} \).
class	QuadraticWeight	Quadratic weight function, scaled using the maximum to reach 0.1 at that point using: \( 1.0 - 0.9 \frac{\text{dist}^2}{\max^2}\} \)