ALL.Regression.FitObj-class: Classes '"KNN.Regression.FitObj"',...

In EnsembleBase: Extensible Package for Parallel, Batch Training of Base Learners for Ensemble Modeling

Description

Objects returned by base learner training functions.

Objects from the Class

Objects can be created by calls of the form new("KNN.Regression.FitObj", ...).

Slots

All classes inherit slots config, est, and pred from "Regression.FitObj". Some base learners may have additional slots as described below.

For KNN.Regression.FitObj:

formula:

Object of class "formula", copy of same argument from training call BaseLearner.Fit.

data:

Object of class "data.frame", copy of same argument from training call BaseLearner.Fit.

For NNET.Regession.FitObj:

y.range:

Object of class "numeric", range of response variable in training data. This is used for scaling of data during prediction so that it falls between 0 and 1 for regression tasks.

y.min:

Object of class "numeric", minimum of response variable in training data. This is used for scaling of data during prediction so that it falls between 0 and 1 for regression tasks.

For PENREG.Regression.FitObj and BART.Regression.FitObj:

mm:

A list containing data structures needed for creating the matrix of predictors and the response variable from the formula and data frame.

Extends

Class "Regression.FitObj", directly. Class "BaseLearner.FitObj", by class "Regression.FitObj", distance 2.

Methods

None.

Author(s)

Alireza S. Mahani, Mansour T.A. Sharabiani

See Also

"BaseLearner.FitObj", "Regression.FitObj"

Examples

showClass("KNN.Regression.FitObj")

EnsembleBase documentation built on May 2, 2019, 2:10 p.m.