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RTextTools (version 1.3.2)

Automatic Text Classification via Supervised Learning

Description

RTextTools is 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 nine algorithms for ensemble classification (svm, slda, boosting, bagging, random forests, glmnet, decision trees, neural networks, maximum entropy), comprehensive analytics, and thorough documentation.

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Version

Install

install.packages('RTextTools')

Monthly Downloads

509

Version

1.3.2

License

GPL-3

Maintainer

Timothy P Jurka

Last Published

December 5th, 2011

Functions in RTextTools (1.3.2)

create_scoreSummary

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

creates a summary with ensemble coverage and precision.
classify_model

makes predictions from a train_model() object.
train_models

makes a model object using the specified algorithms.
USCongress

a sample dataset containing labeled bills from the United State Congress.
analytics_container-class

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

used for cross-validation of various algorithms.
read_data

reads data from files into an R data frame.
RTextTools-package

RTextTools Machine Learning
create_corpus

creates a corpus for training, classifying, and analyzing documents.
create_precisionRecallSummary

creates a summary with precision, recall, and F1 scores.
matrix_container-class

an S4 class containing the training and classification matrices.
create_analytics

creates an object of class analytics given classification results.
print_algorithms

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

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

creates a document-term matrix to be passed into create_corpus().
recall_accuracy

calculates the recall accuracy of the classified data.
wizard_train_classify

a simplified function for training and classifying data.
wizard_read_data

a simplified function for reading data from files.
classify_models

makes predictions from a train_models() object.
train_model

makes a model object using the specified algorithm.
NYTimes

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