Description Usage Arguments Value Author(s)
View source: R/bagging.wrapper.v2.R
Compiles results of ensemble feature selection
1 2 3  bagging.wrapper(X, Y, method, bags, f, aggregation.metric, k.folds, repeats,
res, tuning.grid, optimize, optimize.resample, metric, model.features,
allowParallel, verbose, theDots)

X 
A matrix containing numeric values of each feature 
Y 
A factor vector containing group membership of samples 
method 
A vector listing models to be fit 
bags 
Number of bags to be run 
f 
Number of features desired 
aggregation.metric 
string indicating the type of ensemble aggregation.
Avialable options are 
k.folds 
Number of folds generated during crossvalidation 
repeats 
Number of times crossvalidation repeated 
res 
Optional  Resolution of model optimization grid 
tuning.grid 
Optional list of grids containing parameters to optimize
for each algorithm. Default 
optimize 
Logical argument determining if each model should
be optimized. Default 
optimize.resample 
Logical argument determining if each resample
should be reoptimized. Default 
metric 
Criteria for model optimization. Available options are

model.features 
Logical argument if should have number of features
selected to be determined by the individual model runs.
Default 
allowParallel 
Logical argument dictating if parallel processing
is allowed via foreach package. Default 
verbose 
Logical argument if should output progress 
theDots 
Optional arguments provided for specific models or user
defined parameters if 
results 
List with the following elements: 
Methods: Vector of models fit to data
ensemble.results: List of length = length(method) containing aggregated features
Number.bags: Number of bagging iterations
Agg.metric: Aggregation method applied
Number.features: Number of userdefined features
bestTunes 
If 
Charles Determan Jr
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