ADABOOST | R Documentation |
Ensemble learning, through AdaBoost Algorithm.
ADABOOST(
x,
y,
learningmethod,
nsamples = 100,
fuzzy = FALSE,
tune = FALSE,
seed = NULL,
...
)
x |
The dataset (description/predictors), a |
y |
The target (class labels or numeric values), a |
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.
BAGGING
, predict.boosting
## Not run:
require (datasets)
data (iris)
ADABOOST (iris [, -5], iris [, 5], NB)
## End(Not run)
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