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RTextTools (version 1.4.3)

Automatic Text Classification via Supervised Learning

Description

A machine learning package for automatic text classification that makes it simple for novice users to get started with machine learning, while allowing experienced users to easily experiment with different settings and algorithm combinations. The package includes eight algorithms for ensemble classification (svm, slda, boosting, bagging, random forests, glmnet, decision trees, neural networks), comprehensive analytics, and thorough documentation.

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Version

Install

install.packages('RTextTools')

Monthly Downloads

839

Version

1.4.3

License

GPL-3

Maintainer

Loren Collingwood

Last Published

April 26th, 2020

Functions in RTextTools (1.4.3)

getStemLanguages

Query the languages supported in this package
create_ensembleSummary

creates a summary with ensemble coverage and precision.
create_container

creates a container for training, classifying, and analyzing documents.
read_data

reads data from files into an R data frame.
print_algorithms

prints available algorithms for train_model() and train_models().
matrix_container-class

an S4 class containing the training and classification matrices.
create_scoreSummary

creates a summary with the best label for each document.
train_models

makes a model object using the specified algorithms.
create_precisionRecallSummary

creates a summary with precision, recall, and F1 scores.
wordStem

Get the common root/stem of words
summary.analytics

summarizes the analytics-class class
train_model

makes a model object using the specified algorithm.
recall_accuracy

calculates the recall accuracy of the classified data.
create_matrix

creates a document-term matrix to be passed into create_container().
cross_validate

used for cross-validation of various algorithms.
summary.analytics_virgin

summarizes the analytics_virgin-class class
analytics_virgin-class

an S4 class containing the analytics for a classified set of documents.
NYTimes

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

creates an object of class analytics given classification results.
USCongress

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

makes predictions from a train_models() object.
as.compressed.matrix

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

an S4 class containing the analytics for a classified set of documents.
classify_model

makes predictions from a train_model() object.