ErrorModel: Calculation of an error model
In conformal: Conformal Prediction for Regression and Classification

Description Usage Arguments Value Author(s) References See Also

This function permits the calculation of an error model from (i) a training set, and (ii) a caret model trained on this set to predict the response variable of interest using cross-validation (point prediction model). The cross-validation predictions are extracted from the point prediction model. The errors in prediction for the cross-validation predictions are then calculated. These errors which serve as the response variable for the error model (i.e. the error model predicts errors in prediction). The error model uses as descriptors the same descriptors used to train the point prediction model. These descriptors are input to the function ErrorModel through the argument "x.train".

1	ErrorModel(PointPredictionModel, x.train, algorithm = "svmRadial", ...)

`PointPredictionModel`	Point prediction model from which the cross-validation predictions will be extracted.
`x.train`	Descriptors for the datapoints in the training set used to train the point prediction model, and which will also serve to train the error model.
`algorithm`	The machine learning algorithm to be used to train the error model. The defaul value is Support Vector Machine with radial kernel ("svmRadial").
`...`	Additional arguments that can be passed to the train function from the R package caret to train the error model.