Collects and checks necessary parameters required for classifier training. The empty constructor is provided for convenience.
Creates a default TrainParams object. The classifier function is DLDA. Users
should create an appropriate
TrainParams object for the
characteristics of their data, once they are familiar with this software.
TrainParams(classifier, intermediate = character(0), getFeatures = NULL, ...)
Creates a TrainParams object which stores the function which will do the classifier building and parameters that the function will use.
A function which will construct a classifier, and also
possibly make the predictions. The first argument must be a
object. The second argument must be a vector of classes. If the function also makes predictions
and the value of the
predictor setting of
PredictParams is therefore
the third argument must be a
DataFrame of test data. The function must also accept a
verbose. The function's return value can be either a trained classifier
if the function only does training or a vector or data frame of class predictions if
it also does prediction with the test set samples.
Character vector. Names of any variables created in prior stages by
runTest that need to be passed to
A function may be specified that extracts the selected features from the trained model. This is relevant if using a classifier that does feature selection within training (e.g. random forest). The function must return a list of two vectors. The first vector contains the ranked features (or empty if the training algorithm doesn't produce rankings) and the second vector contains the selected features.
Other named parameters which will be used by the classifier.
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