fuzzyforest (version 1.0.8)

wff.formula: WGCNA based fuzzy forest algorithm

Description

Implements formula interface for wff.

Usage

# S3 method for formula
wff(formula, data = NULL, ...)

Arguments

formula

Formula object.

data

data used in the analysis.

...

Additional arguments

Value

An object of type fuzzy_forest. This object is a list containing useful output of fuzzy forests. In particular it contains a data.frame with list of selected features. It also includes the random forest fit using the selected features.

See Also

wff, print.fuzzy_forest, predict.fuzzy_forest, modplot

Examples

# NOT RUN {
data(ctg)
y <- ctg$NSP
X <- ctg[, 2:22]
dat <- as.data.frame(cbind(y, X))
WGCNA_params <- WGCNA_control(p = 6, minModuleSize = 1, nThreads = 1)
mtry_factor <- 1; min_ntree <- 500;  drop_fraction <- .5; ntree_factor <- 1
screen_params <- screen_control(drop_fraction = drop_fraction,
                                keep_fraction = .25, min_ntree = min_ntree,
                                ntree_factor = ntree_factor,
                                mtry_factor = mtry_factor)
select_params <- select_control(drop_fraction = drop_fraction,
                                number_selected = 5,
                                min_ntree = min_ntree,
                                ntree_factor = ntree_factor,
                                mtry_factor = mtry_factor)
# }
# NOT RUN {
library(WGCNA)
wff_fit <- wff(y ~ ., data=dat,
               WGCNA_params = WGCNA_params,
               screen_params = screen_params,
               select_params = select_params,
               final_ntree = 500)

#extract variable importance rankings
vims <- wff_fit$feature_list

#plot results
modplot(wff_fit)
# }