DF_dataFs: Decision Forest algorithm: Feature Selection in...
In seldas/Dforest: Decision Forest
Description
Usage
Arguments
Value
Description
Decision Forest algorithm: feature selection for two-class predictions,
kept statistical significant features pass the t-test
Usage
1
DF_dataFs(X, Y, p_val = 0.05)
Arguments
X
Training Dataset
Y
Training Labels
p_val
Correlation Coefficient threshold to filter out high correlated features; default is 0.95
Value
Keep_feat: qualified features in data matrix after filtering
seldas/Dforest documentation built on May 30, 2019, 8:08 p.m.
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Description Usage Arguments Value
Description
Decision Forest algorithm: feature selection for two-class predictions, kept statistical significant features pass the t-test
Usage
1 | DF_dataFs(X, Y, p_val = 0.05)
|
Arguments
X |
Training Dataset |
Y |
Training Labels |
p_val |
Correlation Coefficient threshold to filter out high correlated features; default is 0.95 |
Value
Keep_feat: qualified features in data matrix after filtering
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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