NaiveBayes: Naive Bayes Classification and Prediction

#' Tweets dataset
#'
#' This data originally came from Crowdflower's Data for Everyone library
#'
#' "A sentiment analysis job about the problems of each major U.S. airline. Twitter data was scraped from February of 2015 and contributors were asked to first classify positive, negative, and neutral tweets, followed by categorizing negative reasons (such as "late flight" or "rude service")."
#' The data provided here is an altered and cleaned version version of the original source.
#'
#' @format a data frame with 100 rows and 2214 columns.
#'
#' @source \url{https://www.figure-eight.com/data-for-everyone/}
"tweet1"



#' HouseVotes dataset
#'
#' This data set includes votes for each of the U.S. House of Representatives Congressmen on the 16 key votes identified by the CQA.
#'
#' These data have been taken from the UCI Repository Of Machine Learning Databases
#' and were converted to R format by Friedrich Leisch.
#'
#' @format a data frame with 232 rows and 17 columns.
#'
#' @source \url{http://www.ics.uci.edu/~mlearn/MLRepository.html}
"HouseVotes84"