bagging.pred: Wrapper on lazy learning algoritmhs for regression and...

In gbonte/gbcode: Code from the handbook "Statistical foundations of machine learning"

Wrapper on lazy learning algoritmhs for regression and classification

Description

Bagging wrapper on algoritmhs

Usage

bagging.pred(
  algo,
  X,
  Y,
  X.ts,
  B = 10,
  maxN = Inf,
  classi = TRUE,
  balanced = FALSE,
  bagvar = 0,
  ...
)

Arguments

X:	training input
Y:	training output
X.ts:	test input
classi:	TRUE for classification, FALSE for regression
return.more:	TRUE for returning additional lazy parameter

Value

if classi=FALSE predicted test output; if classi=TRUE a list with

• pred: predicted class

• prob: posteriori probability

Author(s)

Gianluca Bontempi [e-mail]

References

mlg.ulb.ac.be

gbonte/gbcode documentation built on Feb. 27, 2024, 7:38 a.m.