| analytics-class | an S4 class containing the analytics for a classified set of documents. |
| analytics_virgin-class | an S4 class containing the analytics for a classified set of documents. |
| as.compressed.matrix | converts a tm DocumentTermMatrix or TermDocumentMatrix into a matrix.csr representation. |
| classify_model | makes predictions from a train_model() object. |
| classify_models | makes predictions from a train_models() object. |
| create_analytics | creates an object of class analytics given classification results. |
| create_container | creates a container for training, classifying, and analyzing documents. |
| create_ensembleSummary | creates a summary with ensemble coverage and precision. |
| create_matrix | creates a document-term matrix to be passed into create_container(). |
| create_precisionRecallSummary | creates a summary with precision, recall, and F1 scores. |
| create_scoreSummary | creates a summary with the best label for each document. |
| cross_validate | used for cross-validation of various algorithms. |
| getStemLanguages | Query the languages supported in this package |
| matrix_container-class | an S4 class containing the training and classification matrices. |
| NYTimes | a sample dataset containing labeled headlines from The New York Times. |
| print_algorithms | prints available algorithms for train_model() and train_models(). |
| read_data | reads data from files into an R data frame. |
| recall_accuracy | calculates the recall accuracy of the classified data. |
| summary.analytics | summarizes the 'analytics-class' class |
| summary.analytics_virgin | summarizes the 'analytics_virgin-class' class |
| train_model | makes a model object using the specified algorithm. |
| train_models | makes a model object using the specified algorithms. |
| USCongress | a sample dataset containing labeled bills from the United State Congress. |
| wordStem | Get the common root/stem of words |