choose_top_features: Choose top features
In mdkessler/kTSCR: Implements k-Top Scoring Cluster Regression
Description
Usage
Arguments
Value
View source: R/choose_top_features.R
Description
Use kmeans clustering to separate features into priority groups based on feature importance scores calculated during n fold k-cv iterations
Usage
1
choose_top_features(vec)
Arguments
vec
a numerical vector of features importance scores. Vector should be named with feature names
Value
a vector of top_features
mdkessler/kTSCR documentation built on Feb. 25, 2021, 10:31 p.m.
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Description Usage Arguments Value
View source: R/choose_top_features.R
Description
Use kmeans clustering to separate features into priority groups based on feature importance scores calculated during n fold k-cv iterations
Usage
1 | choose_top_features(vec)
|
Arguments
vec |
a numerical vector of features importance scores. Vector should be named with feature names |
Value
a vector of top_features
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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