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 |
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.
## Not run: require (datasets) data (iris) ADABOOST (iris [, -5], iris [, 5], NB) ## End(Not run)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.