Spark ML -- Naive-Bayes

Usage

ml_naive_bayes(x, response, features, lambda = 0, ml.options = ml_options(), ...)

Arguments

x
An object coercable to a Spark DataFrame (typically, a tbl_spark).
response
The name of the response vector (as a length-one character vector), or a formula, giving a symbolic description of the model to be fitted. When response is a formula, it is used in preference to other parameters to set the response, features, and intercept parameters (if available). Currently, only simple linear combinations of existing parameters is supposed; e.g. response ~ feature1 + feature2 + .... The intercept term can be omitted by using - 1 in the model fit.
features
The name of features (terms) to use for the model fit.
lambda
The (Laplace) smoothing parameter. Defaults to zero.
ml.options
Optional arguments, used to affect the model generated. See ml_options for more details.
...
Optional arguments; currently unused.

Description

Perform regression or classification using naive bayes.