norm.softmax: Softmax normalisation
In som.nn: Topological k-NN Classifier Based on Self-Organising Maps
norm.softmax R Documentation
Softmax normalisation
Description
Calculates a softmax-like normalisation for the class frequencies.
Usage
norm.softmax(x, t = 0.2)
Arguments
x
vector of votes for classes
t
temperature parameter.
Details
Softmax function is applied to a vector to squeeze the values in a way that they sum up
to 1.0:
som.nn.softmax(x) = exp(x/T) / sum(exp(x/T))
Low values for T result in a
strong separation of output values. High values for T
make output values more equal.
Value
Vector of softmax normalised values.
som.nn documentation built on May 29, 2024, 6:50 a.m.
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| norm.softmax | R Documentation |
Softmax normalisation
Description
Calculates a softmax-like normalisation for the class frequencies.
Usage
norm.softmax(x, t = 0.2)
Arguments
x |
vector of votes for classes |
t |
temperature parameter. |
Details
Softmax function is applied to a vector to squeeze the values in a way that they sum up to 1.0:
som.nn.softmax(x) = exp(x/T) / sum(exp(x/T))
Low values for T result in a
strong separation of output values. High values for T
make output values more equal.
Value
Vector of softmax normalised values.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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