post.prob: Compute posterior probabilities

In renatorrsilva/nb: R/nb: Functions to run the naive Bayes classifier

Description

This is a function to compute posterior probabilities of a new instance to belong to a category given a set of observed features

Usage

  post.prob(object, xnew.quali, xnew.quant)

Arguments

object	is a nb object.
xnew.quali	is a vector which contains qualitative/discrete features of the new instance
xnew.quant	is a vector which contains quantitative features of the new instance

Value

The output is a vector with posterior probability of new instance for each category.

Author(s)

Renato Rodrigues Silva, [e-mail]

Examples

data(seeds)
mod =  naive.bayes(x=seeds, ct="varieties")
xnew1 = unlist(seeds[1,])[-8]
post.prob(mod,xnew.quant=xnew1)

renatorrsilva/nb documentation built on May 30, 2019, 6:14 p.m.