DaMiR.EnsL_Test {DaMiRseq} | R Documentation

## Test Binary Classifiers

### Description

This function tests the models learned by the DaMiR.EnsL_Train function, on a test set

### Usage

    DaMiR.EnsL_Test(data, classes, EnsL_model)

### Arguments

`data` | A SummarizedExperiment object or a data frame/matrix of normalized expression data. Rows and Cols should be observations and features, respectively.
`classes` | A class vector with `nrow(data)` elements. Each element represents the class label for each observation. Two different class labels are allowed. Note. this argument should not be set when 'data' is a SummarizedExperiment object
`EnsL_model` | A list with the models trained by DaMiR.EnsL_Train function.

### Details

This function implements the test step of DaMiR.EnsembleLearning2cl function

### Value

A dataframe containing the predictions on the testset

### Author(s)

Mattia Chiesa, Luca Piacentini

### Examples

    # 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.EnsL_Train(
    #  selected_features,classes=df$class, fSample.tr.w=0.6, iter=3,
    # cl_type=c("RF","LR"))
    # DaMiR.EnsembleLearning2cl_Test(selected_features,
    #classes=df$class,Tr_res)

[Package DaMiRseq version 2.6.0 Index]