naiveBayes_likelihood: Naive Bayes likelihood

In tatters/soundgen: Sound Synthesis and Acoustic Analysis

Naive Bayes likelihood

Description

Internal soundgen function

Usage

naiveBayes_likelihood(
  d,
  nObs = nrow(d),
  mod_train,
  class_names,
  nClasses = length(class_names),
  like_names,
  predictors,
  nPredictors = length(predictors)
)

Arguments

d	dataframe containing the observations
nObs	the number of observations
mod_train	the output of naiveBayes_train()
class_names	names of outcome classes
nClasses	the number of outcome classes
like_names	the names of variables holding likelihoods
predictors	the names of predictor variables
nPredictors	the number of predicto variables

Details

A Helper function called by naiveBayes to calculate the likelihood of each observation. Algorithm: for each predictor and class, the likelihood is dnorm(observation, mean_per_class, sd_per_class). I tried non-Gaussian probability distributions (Student's t to accommodate outliers), but Gaussian actually seems to be more robust.

tatters/soundgen documentation built on Aug. 22, 2023, 4:24 p.m.