predict.textVectors: Take a sparse text matrix and construct a matric with the...

In zachmayer/r2vec: Text data to numeric vectors

Description

This code takes an existing sparse text matrix, and a character vector of new data. It then tokenizes the new data, spellchecks it (todo), applies n-grams, and uses the bag of words from the input matrix to contruct a new matrix with the exact same columns. It then optionally applies the input matrix's tf-idf weightings to the new matrix and returns a new textVectors object. TODO: COMBINE THIS WITH THE MATRIX FUNCTION!!!

Usage

## S3 method for class 'textVectors'
predict(object, newdata = NULL, verbose = FALSE, ...)

Arguments

object	object of class textVectors
newdata	new data to apply the same matrix format to
verbose	print diagnostic messages
...	ignored

Value

a textVectors object

References

http://stackoverflow.com/questions/4942361/how-to-turn-a-list-of-lists-to-a-sparse-matrix-in-r-without-using-lapply http://en.wikipedia.org/wiki/Tf-idf

Examples

x <- c(
  'i like this package written by zach mayer',
  'this package is so much fun',
  'thanks zach for writing it',
  'this package is the best package',
  'i want to give zach mayer a million dollars')
y <- 'this is a new sentence about how much i like this package written
by zach mayer it is a cool package and he is a cool dude'
a <- textVectors(
  x,
  absCutoff=1, ngrams=2, stem=TRUE, verbose=TRUE)
b <- textVectors(
  x,
  absCutoff=1, ngrams=2, stem=TRUE, verbose=TRUE, tfidf=TRUE)
predict(a, y)
predict(b, y)

zachmayer/r2vec documentation built on May 4, 2019, 9:05 p.m.