Description Details Author(s) References Examples
maxent is an R package with tools for low-memory multinomial logistic regression, also known as maximum entropy. The focus of this maximum entropy classifier is to minimize memory consumption on very large datasets, particularly sparse document-term matrices represented by the tm package. The library is built on top of an efficient C++ implementation written by Yoshimasa Tsuruoka.
Package: | maxent |
Type: | Package |
Version: | 1.3.3 |
Date: | 2013-04-06 |
License: | GPL-3 |
LazyLoad: | yes |
Timothy P. Jurka <tpjurka@ucdavis.edu>
Y. Tsuruoka. "A simple C++ library for maximum entropy classification." University of Tokyo Department of Computer Science (Tsujii Laboratory), 2011. URL http://www-tsujii.is.s.u-tokyo.ac.jp/~tsuruoka/maxent/.
1 2 3 4 5 6 7 8 9 10 11 12 | # 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$Title[1:150]))
matrix <- DocumentTermMatrix(corpus)
# TRAIN/PREDICT USING SPARSEM REPRESENTATION
sparse <- as.compressed.matrix(matrix)
model <- maxent(sparse[1:100,],data$Topic.Code[1:100])
results <- predict(model,sparse[101:150,])
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