as.compressed.matrix: converts a tm DocumentTermMatrix or TermDocumentMatrix into a...

In maxent: Low-memory Multinomial Logistic Regression with Support for Text Classification

Description

Converts a DocumentTermMatrix or TermDocumentMatrix (package tm), Matrix (package Matrix), matrix.csr (SparseM), data.frame, or matrix into a matrix.csr representation to be used in the maxent and predict.maxent functions.

Usage

as.compressed.matrix(DocumentTermMatrix)

Arguments

DocumentTermMatrix

A class of type DocumentTermMatrix or TermDocumentMatrix (package tm), Matrix (package Matrix), matrix.csr (SparseM), data.frame, or matrix.

Value

A matrix.csr representation of the DocumentTermMatrix or TermDocumentMatrix (package tm), Matrix (package Matrix), matrix.csr (SparseM), data.frame, or matrix.

Author(s)

Timothy P. Jurka <[e-mail]>

Examples

# LOAD LIBRARY
library(maxent)

# READ THE DATA, PREPARE THE CORPUS, and CREATE THE MATRIX
data <- read.csv(system.file("data/NYTimes.csv.gz",package="maxent"))
corpus <- Corpus(VectorSource(data$Title[1:150]))
matrix <- DocumentTermMatrix(corpus)

# CREATE A MATRIX.CSR (SPARSEM) REPRESENTATION
sparse <- as.compressed.matrix(matrix)

Example output

Loading required package: SparseM

Attaching package: 'SparseM'

The following object is masked from 'package:base':

    backsolve

Loading required package: tm
Loading required package: NLP

maxent documentation built on May 29, 2017, 1:40 p.m.