PredictParams-class: Parameters for Classifier Prediction

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

Parameters for Classifier Prediction

Description

Collects the function to be used for making predictions and any associated parameters.

Details

The function specified must return either a factor vector of class predictions, or a numeric vector of scores for the second class, according to the levels of the class vector of the input data set, or a data frame which has two columns named class and score.

Constructor

PredictParams(predictor, characteristics = DataFrame(), intermediate = character(0), ...)

Creates a PredictParams object which stores the function which will do the class prediction, if required, and parameters that the function will use. If the training function also makes predictions, this must be set to NULL.

predictor

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

characteristics

A DataFrame describing the characteristics of the predictor function used. First column must be named "charateristic" and second column must be named "value".

intermediate

Character vector. Names of any variables created in prior stages in runTest that need to be passed to the prediction function.

...

Other arguments that predictor may use.

Summary

predictParams is a PredictParams object.

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

Author(s)

Dario Strbenac

Examples

# For prediction by trained object created by DLDA training function.
predictParams <- PredictParams("DLDA")

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