Package | Description |
---|---|
de.lmu.ifi.dbs.elki.math.linearalgebra.pca |
Principal Component Analysis (PCA) and Eigenvector processing.
|
de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions |
Weight functions used in weighted PCA via
WeightedCovarianceMatrixBuilder |
Modifier and Type | Field and Description |
---|---|
protected WeightFunction |
WeightedCovarianceMatrixBuilder.weightfunction
Holds the weight function.
|
protected WeightFunction |
WeightedCovarianceMatrixBuilder.Parameterizer.weightfunction
Weight function.
|
Constructor and Description |
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WeightedCovarianceMatrixBuilder(WeightFunction weightfunction)
Constructor.
|
Modifier and Type | Class and Description |
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class |
ConstantWeight
Constant Weight function
The result is always 1.0
|
class |
ErfcStddevWeight
Gaussian Error Function Weight function, scaled using stddev.
|
class |
ErfcWeight
Gaussian Error Function Weight function, scaled such that the result it 0.1
at distance == max
erfc(1.1630871536766736 * distance / max)
The value of 1.1630871536766736 is erfcinv(0.1), to achieve the intended
scaling.
|
class |
ExponentialStddevWeight
Exponential Weight function, scaled such that the result it 0.1 at distance
== max
stddev * exp(-.5 * distance/stddev)
This is similar to the Gaussian weight function, except distance/stddev is
not squared.
|
class |
ExponentialWeight
Exponential Weight function, scaled such that the result it 0.1 at distance
== max
exp(-2.3025850929940455 * distance/max)
This is similar to the Gaussian weight function, except distance/max is not
squared
|
class |
GaussStddevWeight
Gaussian Weight function, scaled such using standard deviation
factor * exp(-.5 * (distance/stddev)^2)
with factor being 1 / sqrt(2 * PI)
|
class |
GaussWeight
Gaussian Weight function, scaled such that the result it 0.1 at distance ==
max
exp(-2.3025850929940455 * (distance/max)^2)
|
class |
InverseLinearWeight
Inverse Linear Weight Function.
|
class |
InverseProportionalStddevWeight
Inverse proportional weight function, scaled using the standard deviation.
1 / (1 + distance/stddev)
|
class |
InverseProportionalWeight
Inverse proportional weight function, scaled using the maximum.
1 / (1 + distance/max)
|
class |
LinearWeight
Linear weight function, scaled using the maximum such that it goes from 1.0
to 0.1
1 - 0.9 * (distance/max)
|
class |
QuadraticStddevWeight
Quadratic weight function, scaled using the standard deviation.
|
class |
QuadraticWeight
Quadratic weight function, scaled using the maximum to reach 0.1 at that
point.
1.0 - 0.9 * (distance/max)^2
|
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.