TrainParams-class: Parameters for Classifier Training

In DarioS/ClassifyR: A framework for cross-validated classification problems, with applications to differential variability and differential distribution testing

Parameters for Classifier Training

Description

Collects and checks necessary parameters required for classifier training. The empty constructor is provided for convenience.

Constructor

TrainParams(classifier, balancing = c("downsample", "upsample", "none"), characteristics = DataFrame(), intermediate = character(0), tuneParams = NULL, getFeatures = NULL, ...)

Creates a TrainParams object which stores the function which will do the classifier building and parameters that the function will use.

classifier

A character keyword referring to a registered classifier. See available for valid keywords.

balancing

Default: "downsample". A keyword specifying how to handle class imbalance for data sets with categorical outcome. Valid values are "downsample", "upsample" and "none".

characteristics

A DataFrame describing the characteristics of the classifier used. First column must be named "charateristic" and second column must be named "value". If using wrapper functions for classifiers in this package, a classifier name will automatically be generated and therefore it is not necessary to specify it.

intermediate

Character vector. Names of any variables created in prior stages by runTest that need to be passed to classifier.

tuneParams

A list specifying tuning parameters required during feature selection. The names of the list are the names of the parameters and the vectors are the values of the parameters to try. All possible combinations are generated.

getFeatures

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.

Summary

trainParams is a TrainParams object.

show(trainParams): Prints a short summary of what trainParams contains.

Author(s)

Dario Strbenac

Examples

#if(require(sparsediscrim))
  trainParams <- TrainParams("DLDA")

DarioS/ClassifyR documentation built on Nov. 4, 2024, 1:06 p.m.