Description Usage Arguments Value Note References Examples
Creates screen_control
object for
controlling how feature selection
will be carried out on each module.
1 2 | screen_control(drop_fraction = 0.25, keep_fraction = 0.05,
mtry_factor = 1, min_ntree = 5000, ntree_factor = 10)
|
drop_fraction |
A number between 0 and 1. Percentage of features dropped at each iteration. |
keep_fraction |
A number between 0 and 1. Proportion of features from each module that are retained from screening step. |
mtry_factor |
In the case of regression, |
min_ntree |
Minimum number of trees grown in each random forest. |
ntree_factor |
A number greater than 1. |
An object of type screen_control.
This work was partially funded by NSF IIS 1251151.
Daniel Conn, Tuck Ngun, Christina M. Ramirez (2015). Fuzzy Forests: a New WGCNA Based Random Forest Algorithm for Correlated, High-Dimensional Data, Journal of Statistical Software, Manuscript in progress.
1 2 3 4 5 6 7 8 9 10 | drop_fraction <- .25
keep_fraction <- .1
mtry_factor <- 1
min_ntree <- 5000
ntree_factor <- 5
screen_params <- screen_control(drop_fraction=drop_fraction,
keep_fraction=keep_fraction,
mtry_factor=mtry_factor,
min_ntree=min_ntree,
ntree_factor=ntree_factor)
|
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