#' Predict continuous valued outputs associated with text documents.
#'
#' Predict continuous valued outputs associated with text documents. The input
#' corpus of text documents is transformed into a document-term matrix (DTM)
#' and then a regularized linear regression is fit that uses this matrix as
#' predictors to predict the continuous valued output. The corpus's terms,
#' coefficients for all terms and an estimate of the model's predictive
#' power are returned in a list.
#'
#' @references This code is inspired by Noah Smith's work.
#' @docType package
#' @name TextRegression
#' @aliases TextRegression package-TextRegression
#' @examples
#' library('TextRegression')
#'
#' library('TextRegression')
#'
#' text <- c('saying text is good',
#' 'saying text once and saying text twice is better',
#' 'saying text text text is best',
#' 'saying text once is still ok',
#' 'not saying it at all is bad',
#' 'because text is a good thing',
#' 'we all like text',
#' 'even though sometimes it is missing')
#'
#' y <- c(1, 2, 3, 1, 0, 1, 1, 0)
#'
#' results <- regress.text(text, y)
#'
#' print(results)
NULL
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