classify.dtm: Creates a Document/Term Matrix

In mananshah99/sentR: Provides varied techniques for big data sentiment analysis in R

Description

Provides a utility function used to create a document/term matrix using the package tm

Usage

classify.dtm(sentences, language = "english", minDocFreq = 1,
  minWordLength = 4, removeNumbers = TRUE, removePunctuation = TRUE,
  removeStopwords = TRUE, stemWords = FALSE, stripWhitespace = TRUE,
  toLower = TRUE, weighting = weightTf)

Arguments

sentences	a character vector of sentences to use for training
language	the language to use for word stemming
minDocFreq	the minimum number of times a word is needed in a document to be included in the analysis
minWordLength	the minimnum word length for inclusion in analysis
removeNumbers	a boolean regarding whether numbers whould be removed
removeStopwords	a boolean specifying whether stopwords in the specified language should be removed
stemWords	a boolean specying whether words should be stemmed to their root form in the language specified
stripWhitespace	a boolean indicating whether whitespace should be stripped
toLower	a boolean indicating whether all words should be transformed to their lowercase representations
weighting	either weightTf or weightIfIdf (see the package tm for details)
removePuncutation	a boolean specifying whether to remove puncutation

Examples

classify.dtm(c("I am happy", "I am sad", "I am miserable", "The weather is good today"))

mananshah99/sentR documentation built on May 21, 2019, 11:23 a.m.