reduce.dictionary: reduce the dictionary size hierarchically
In ConvergenceDA/visdomloadshape: R package for load shape clustering and analysis, extending the visdom package
Description
uses k nearest neighbors (class::knn) to reduce the size of the passed dictionary to a target number of entries by merging the most similar clusters.
Usage
1
reduce.dictionary(dic, cl.size, t.num = 1000, d.metric = 1)
Arguments
dic
dictionary(=cluster centers) /
cl.size
size of each cluster /
t.num
target dictionary size
d.metric
distance metric to use for similarity comparison == 1: Euclidean, ==2: Cosine
ConvergenceDA/visdomloadshape documentation built on May 8, 2019, 8:34 a.m.
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Description
uses k nearest neighbors (class::knn) to reduce the size of the passed dictionary to a target number of entries by merging the most similar clusters.
Usage
1 | reduce.dictionary(dic, cl.size, t.num = 1000, d.metric = 1)
|
Arguments
dic |
dictionary(=cluster centers) / |
cl.size |
size of each cluster / |
t.num |
target dictionary size |
d.metric |
distance metric to use for similarity comparison == 1: Euclidean, ==2: Cosine |
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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