skcla_nb {daltoolboxdp} | R Documentation |
Gaussian Naive Bayes Classifier
Description
Implements classification using the Gaussian Naive Bayes algorithm. This function wraps the GaussianNB from Python's scikit-learn library.
Usage
skcla_nb(attribute, slevels, var_smoothing = 1e-09, priors = NULL)
Arguments
attribute |
Target attribute name for model building |
slevels |
List of possible values for classification target |
var_smoothing |
Portion of the largest variance of all features that is added to variances |
priors |
Prior probabilities of the classes. If specified must be a list of length n_classes |
Details
Naive Bayes Classifier
Value
A Naive Bayes classifier object
skcla_nb
object
Examples
#See an example of using `skcla_nb` at this
#https://github.com/cefet-rj-dal/daltoolboxdp/blob/main/examples/skcla_nb.md
[Package daltoolboxdp version 1.2.707 Index]