make_RF_model: model training

In xiangpin/MetaMicrobiome: An R package for meta-analysis and visualization of Microbiome.

Description

build a model with training datasets.

Usage

make_RF_model(train_data, study, numtree = 500, number_try,
  numbercv = 10, classvariable)

Arguments

train_data	list or dataframe, the dataframe contianed the features or a list contianed multi-dataframe with features.
study	character,if train_data is a list, we can use 'study' extract the dataframe, default is NULL.
numtree	numeric, the number of trees for randomforest, see [randomForest] details.
number_try	numeric, the number of variables randomly sampled as candidates at each split, see [randomForest] details, default is 'round(sqrt(ncol(train_data)))'.
numbercv	numeric, the number of cross-validation.
classvariable	character, the header name of the train dataframe for the classification.

Details

TODO

Value

a model object, see [randomForest] details.

Author(s)

Shuangbin Xu

xiangpin/MetaMicrobiome documentation built on May 26, 2019, 2:34 a.m.