nb2: nb2: Extended Naive Bayes - Updateable Version
In aschersleben/NBCD: Naive Bayes for Online Classification with Concept Drift

Description Usage Arguments Value Author(s) See Also Examples

Modified and extended copy of naiveBayes from e1071.

1	nb2(x, y, laplace = 0, discretize, discParams, ...)

`x`	`[matrix \| data.frame]` A numeric matrix, or a data frame of categorical and/or numeric variables.
`y`	`[numeric \| factor \| character]` Class vector.
`laplace`	`[numeric(1)]` positive double controlling Laplace smoothing. The default (0) disables Laplace smoothing.
`discretize`	`[character(1)]` If missing: No discretization will be performed and discParams argument is ignored. If "fixed": number of intervals or there boundaries have to be given in the discParam argument
`discParams`	`[numeric \| list]` If discretize = "fixed": Has to be a named list giving the boundaries for the variables to be discretized.
`...`	Currently ignored.

[nb2]
additional element: "yc" contains Youngs-Cramer variance parameters

David Meyer David.Meyer@R-project.org: original naiveBayes
Philipp Aschersleben aschersleben@statistik.tu-dortmund.de: modifications and extensions for the NBCD package

update.nb2, plot.nb2, print.nb2, predict.nb2

mod <- nb2(iris[, 1:4], iris[, 5])
mod

# Example for easy discretization:
discParam <- list(Sepal.L = c(5, 6, 7), Sepal.W = c(2.5, 3.5))
mod2 <- nb2(iris[, 1:4], iris[, 5], discretize = "fixed", discParams = discParam)
mod2