WeightedCovarianceMatrixBuilder
See: Description
Interface | Description |
---|---|
WeightFunction |
WeightFunction interface that allows the use of various distance-based weight
functions.
|
Class | Description |
---|---|
ConstantWeight |
Constant Weight function
The result is always 1.0
|
ErfcStddevWeight |
Gaussian Error Function Weight function, scaled using stddev.
|
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.
|
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.
|
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
|
GaussStddevWeight |
Gaussian weight function, scaled using standard deviation
\( 1/\sqrt(2\pi) \exp(-\frac{\text{dist}^2}{2\sigma^2}) \)
|
GaussWeight |
Gaussian weight function, scaled such that the result it 0.1 at distance ==
max, using \( \exp(-2.3025850929940455 \frac{\text{dist}^2}{\max^2}) \).
|
InverseLinearWeight |
Inverse Linear Weight Function.
|
InverseProportionalStddevWeight |
Inverse proportional weight function, scaled using the standard deviation.
1 / (1 + distance/stddev)
|
InverseProportionalWeight |
Inverse proportional weight function, scaled using the maximum.
1 / (1 + distance/max)
|
LinearWeight |
Linear weight function, scaled using the maximum such that it goes from 1.0
to 0.1
1 - 0.9 * (distance/max)
|
QuadraticStddevWeight |
Quadratic weight function, scaled using the standard deviation.
|
QuadraticWeight |
Quadratic weight function, scaled using the maximum to reach 0.1 at that
point.
|
WeightedCovarianceMatrixBuilder
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