RTextTools (version 1.3.2)

recall_accuracy: calculates the recall accuracy of the classified data.

Description

Given the true labels to compare to the labels predicted by the algorithms, calculates the recall accuracy of each algorithm.

Usage

recall_accuracy(true_labels, predicted_labels)

Arguments

true_labels

A vector containing the true labels, or known values for each document in the classification set.

predicted_labels

A vector containing the predicted labels, or classified values for each document in the classification set.

Examples

library(RTextTools)
data <- read_data(system.file("data/NYTimes.csv.gz",package="RTextTools"),type="csv")
data <- data[sample(1:3100,size=100,replace=FALSE),]
matrix <- create_matrix(cbind(data$Title,data$Subject), language="english", 
removeNumbers=TRUE, stemWords=FALSE, weighting=weightTfIdf)
corpus <- create_corpus(matrix,data$Topic.Code,trainSize=1:75, testSize=76:100, 
virgin=FALSE)
models <- train_models(corpus, algorithms=c("MAXENT","SVM"))
results <- classify_models(corpus, models)
analytics <- create_analytics(corpus, results)
recall_accuracy(analytics@document_summary$MANUAL_CODE,
analytics@document_summary$GLMNET_LABEL)
recall_accuracy(analytics@document_summary$MANUAL_CODE,
analytics@document_summary$MAXENTROPY_LABEL)
recall_accuracy(analytics@document_summary$MANUAL_CODE,
analytics@document_summary$SVM_LABEL)