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 |