Usage
train_classifier(dataset, column.class, model, validation,
num.folds = 10, num.repeats = 10, tunelength = 10,
tunegrid = NULL, metric = NULL,
summary.function = defaultSummary, class.in.metadata = T)
Arguments
dataset
list representing the dataset from a metabolomics experiment.
column.class
metadata column class.
model
model to be used in training.
validation
validation method.
num.folds
number of folds in cross validation.
num.repeats
number of repeats.
tunelength
number of levels for each tuning parameters.
tunegrid
dataframe with possible tuning values.
metric
metric used to evaluate the model's performance. Can be "Accuracy" or "ROC".
summary.function
summary function. For "ROC" the multiClassSummary function must be used.
class.in.metadata
boolean value to indicate if the class is in metadata.