infix_class_prob: Predict Method for Family of Naive Bayes Objects
In naivebayes: High Performance Implementation of the Naive Bayes Algorithm

Description Usage Arguments Details Value Author(s) See Also Examples

The infix operators %class% and %prob% are shorthands for performing classification and obtaining posterior probabilities, respectively.

1 2	lhs %class% rhs lhs %prob% rhs

`lhs`	object of class inheriting from `"naive_bayes"` and `"*_naive_bayes"` family.
`rhs`	dataframe or matrix for "naive_bayes" objects OR matrix for all "*_naive_bayes" objects.

If lhs is of class inheriting from the family of the Naive Bayes objects and rhs is either dataframe or matrix then the infix operators %class% and %prob% are equivalent to:

lhs %class% rhs <=> predict(lhs, newdata = rhs, type = "class", threshold = 0.001, eps = 0)
lhs %prob% rhs <=> predict(lhs, newdata = rhs, type == "prob", threshold = 0.001, eps = 0)

Compared to predict(), both operators do not allow changing values of fine tuning parameters threshold and eps.

%class% returns factor with class labels corresponding to the maximal conditional posterior probabilities.
%prob% returns a matrix with class label specific conditional posterior probabilities.

Michal Majka, michalmajka@hotmail.com

predict.naive_bayes, predict.bernoulli_naive_bayes, predict.multinomial_naive_bayes, predict.poisson_naive_bayes, predict.gaussian_naive_bayes, predict.nonparametric_naive_bayes

### Fit the model
nb <- naive_bayes(Species ~ ., iris)

newdata <- iris[1:5,-5] # Let's pretend

### Classification
nb %class% newdata
predict(nb, newdata, type = "class")

### Posterior probabilities
nb %prob% newdata
predict(nb, newdata, type = "prob")