reg: Regression Methods

In SkadiEye/ITRlearn: Individualized Treatment Rule Learning

Description

A collection of functions to build regression models.

Usage

regLASSO(object, valid = NULL, ...)

regSVR(object, valid = NULL, ...)

regRF(object, valid = NULL, ...)

regANN(object, valid = NULL, ...)

regDNN(object, valid = NULL, ...)

## S4 method for signature 'RegObj'
regLASSO(object, valid = NULL, ...)

## S4 method for signature 'RegObj'
regSVR(object, valid = NULL, ...)

## S4 method for signature 'RegObj'
regRF(object, valid = NULL, ...)

## S4 method for signature 'RegObj'
regANN(object, valid = NULL, ...)

## S4 method for signature 'RegObj'
regDNN(object, valid = NULL, ...)

Arguments

object	A regObj object, used as a training set.
valid	A wClsObj object, used as a validation set.
...	Arguments passed to the function being called.

Details

These reg methods construct a single regression model given a regObj and a set of parameters. This function returns a ModelObj.

Value

Returns a ModelObj object.

Methods (by generic)

regLASSO: Method to build a regression model using glmnet::glmnet.

regSVR: Method to build a regression model using e1071::svm.

regRF: Method to build a regression model using randomForest::randomForest.

regANN: Method to build a regression model using nnet::nnet.

regDNN: Method to build a deep neural network regression model using nn.regresser function.

See Also

reg
wcls
cvGrid
cvKfold
workflow

SkadiEye/ITRlearn documentation built on May 24, 2019, 1:31 a.m.