Classing_prune_clusters: Prune clusters keeping only the most informative variables
In Zelazny7/binnr: Scorecard modeling in R
Description
Prune clusters keeping only the most informative variables
Arguments
cc
classing_cluster object produced by Classing_cluster
method
corr
minimum correlation coefficient threshold with which to group
variables
n
number of variables to keep from each cluster exceeding the
correlation threshold. The n variables with the highest information value
are retained. The remaining variables are returned as a character vector.
Value
a character vector of variables to drop
Zelazny7/binnr documentation built on May 10, 2019, 1:55 a.m.
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Description
Prune clusters keeping only the most informative variables
Arguments
cc |
classing_cluster object produced by |
corr |
minimum correlation coefficient threshold with which to group variables |
n |
number of variables to keep from each cluster exceeding the correlation threshold. The n variables with the highest information value are retained. The remaining variables are returned as a character vector. |
Value
a character vector of variables to drop
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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