naiveBayes_likelihood {soundgen} | R Documentation |
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.
[Package soundgen version 2.7.0 Index]