| DaMiR.EnsembleLearning2cl_Predict {DaMiRseq} | R Documentation |
The models learned by the DaMiR.EnsembleLearning2cl_Training functionn are applied to a dataset, in order to predict the samples class
DaMiR.EnsembleLearning2cl_Predict(data, models_List)
data |
A data frame of normalized expression data. Rows and Cols should be, respectively, observations and features |
models_List |
A list with the models trained by DaMiR.EnsembleLearning2cl_Training function. |
This function implements the test step of DaMiR.EnsembleLearning2cl function
A dataframe containing the predictions
Mattia Chiesa, Luca Piacentini
# use example data:
data(selected_features)
data(df)
set.seed(1)
# only for the example:
# speed up the process setting a low 'iter' argument value;
# for real data set use default 'iter' value (i.e. 100) or higher:
# Tr_res <- DaMiR.EnsembleLearning2cl_Training(
# selected_features,classes=df$class, fSample.tr.w=0.6, iter=3,
# cl_type=c("RF","LR"))
# DaMiR.EnsembleLearning2cl_Predict(selected_features, Tr_res)