Usage
train_models_performance(dataset, models, column.class,
validation, num.folds = 10, num.repeats = 10, tunelength = 10,
tunegrid = NULL, metric = NULL, summary.function = "default",
class.in.metadata = T, compute.varimp = T)
Arguments
dataset
list representing the dataset from a metabolomics experiment.
models
models to be used in training.
column.class
metadata column class.
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.
compute.varimp
boolean value to indicate if the var importance is calculated.