predict.epcreg

Object of class <code>"epcreg"</code>, typically the output of function <code><a rd-options="" href="/link/epcreg?package=EnsemblePCReg&version=1.1.4" data-mini-rdoc="EnsemblePCReg::epcreg">epcreg</a></code>.

object

New data frame to make predictions for. If <code>NULL</code>, prediction is made for training data.

newdata

Number of cores to use for parallel prediction.

ncores

Boolean flag, indicating whether base learner training jobs must be scheduled statically (<code>TRUE</code>) or dynamically (<code>FALSE</code>).

preschedule

Arguments passed to/from other methods.

Obtain model predictions from training or new data for <code>epcreg</code> model.

Extends the base classes and methods of 'EnsembleBase' package for Principal-Components-Regression-based (PCR) integration of base learners. Default implementation uses cross-validation error to choose the optimal number of PC components for the final predictor. The package takes advantage of the file method provided in 'EnsembleBase' package for writing estimation objects to disk in order to circumvent RAM bottleneck. Special save and load methods are provided to allow estimation objects to be saved to permanent files on disk, and to be loaded again into temporary files in a later R session. Users and developers can extend the package by extending the generic methods and classes provided in 'EnsembleBase' package as well as this package.

Alireza Mahani

EnsemblePCReg

Extensible Package for Principal-Component-Regression-Based
Heterogeneous Ensemble Meta-Learning

predict.epcreg function

Object of class <code>"epcreg"</code>, typically the output of function <code><a rd-options='' href='epcreg'>epcreg</a></code>.

predict.epcreg: Predict method for class `"epcreg"`

Description

Usage

Arguments

Value