create_scoreSummary: creates a summary with the best label for each document.

In RTextTools: Automatic Text Classification via Supervised Learning

Description

Creates a summary with the best label for each document, determined by highest algorithm certainty, and highest consensus (i.e. most number of algorithms agreed).

Usage

create_scoreSummary(container, classification_results)

Arguments

container	Class of type matrix_container-class generated by the create_container function.
classification_results	A cbind() of result objects returned by classify_model, or the object returned by classify_models.

Author(s)

Timothy P. Jurka <[e-mail]>, Loren Collingwood <[e-mail]>

Examples

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("RF","SVM"))
results <- classify_models(container, models)
score_summary <- create_scoreSummary(container, results)

RTextTools documentation built on April 26, 2020, 9:05 a.m.