recall_accuracy: calculates the recall accuracy of the classified data.

Description Usage Arguments Author(s) Examples

Description

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

Usage

1
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.

Author(s)

Loren Collingwood <lorenc2@uw.edu>, Timothy P. Jurka <tpjurka@ucdavis.edu>

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
library(RTextTools)
data(NYTimes)
data <- NYTimes[sample(1:3100,size=100,replace=FALSE),]
matrix <- create_matrix(cbind(data["Title"],data["Subject"]), language="english", 
removeNumbers=TRUE, stemWords=FALSE, weighting=tm::weightTfIdf)
container <- create_container(matrix,data$Topic.Code,trainSize=1:75, testSize=76:100, 
virgin=FALSE)
models <- train_models(container, algorithms=c("MAXENT","SVM"))
results <- classify_models(container, models)
analytics <- create_analytics(container, results)
recall_accuracy(analytics@document_summary$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)


Search within the RTextTools package
Search all R packages, documentation and source code

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.