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maxent (version 1.3.3.1)

Low-memory Multinomial Logistic Regression with Support for Text Classification

Description

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 classifier is based on an efficient C++ implementation written by Dr. Yoshimasa Tsuruoka.

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Version

Install

install.packages('maxent')

Monthly Downloads

111

Version

1.3.3.1

License

GPL-3

Maintainer

Last Published

November 14th, 2013

Functions in maxent (1.3.3.1)

USCongress

a sample dataset containing labeled bills from the United State Congress.
tune.maxent

fits a maximum entropy model given a training matrix and a vector or factor of labels.
save.model

saves a maximum entropy model to a file.
as.compressed.matrix

converts a tm DocumentTermMatrix or TermDocumentMatrix into a matrix.csr representation.
maxent-class

an S4 class containing the trained maximum entropy model.
maxent

trains a maximum entropy model given a training matrix and a vector or factor of labels.
NYTimes

a sample dataset containing labeled headlines from The New York Times.
load.model

loads a maximum entropy model from a file.
maxent-package

Low-memory Multinomial Logistic Regression with Support for Text Classification
predict.maxent

predicts the expected label of a document given a trained model.