norm.linear: Linear normalisation
In som.nn: Topological k-NN Classifier Based on Self-Organising Maps
Description
Usage
Arguments
Details
Value
Description
Calculates a linear normalisation for the class frequencies.
Usage
1
norm.linear(x)
Arguments
x
vector of votes for classes
Details
The function is applied to a vector to squeeze the values in a way that they sum up
to 1.0:
som.nn.linnorm(x) = x / sum(x)
Linear normalisation is used to normalise class distrubution during
prediction. Results seems often more reasonable, compared to softmax. The
S4 predict function for Class SOMnn allows to specify
the normalisation function as parameter.
Value
Vector of normalised values.
som.nn documentation built on May 2, 2019, 8:26 a.m.
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Description Usage Arguments Details Value
Description
Calculates a linear normalisation for the class frequencies.
Usage
1 | norm.linear(x)
|
Arguments
x |
vector of votes for classes |
Details
The function is applied to a vector to squeeze the values in a way that they sum up to 1.0:
som.nn.linnorm(x) = x / sum(x)
Linear normalisation is used to normalise class distrubution during
prediction. Results seems often more reasonable, compared to softmax. The
S4 predict function for Class SOMnn allows to specify
the normalisation function as parameter.
Value
Vector of 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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