fdm2id: ADABOOST – R documentation

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ADABOOST

Classification using AdaBoost

Ensemble learning, through AdaBoost Algorithm.

ADABOOST(
  x,
  y,
  learningmethod,
  nsamples = 100,
  fuzzy = FALSE,
  tune = FALSE,
  seed = NULL,
  ...
)

`x`	The dataset (description/predictors), a `matrix` or `data.frame`.
`y`	The target (class labels or numeric values), a `factor` or `vector`.
`learningmethod`	The boosted method.
`nsamples`	The number of samplings.
`fuzzy`	Indicates whether or not fuzzy classification should be used or not.
`tune`	If true, the function returns paramters instead of a classification model.
`seed`	A specified seed for random number generation.
`...`	Other specific parameters for the leaning method.

The classification model.

## Not run: 
require (datasets)
data (iris)
ADABOOST (iris [, -5], iris [, 5], NB)

## End(Not run)

Data Mining and R Programming for Beginners

v0.9.5

GPL-3

Authors

Alexandre Blansché [aut, cre]

Initial release