I was going through this example of maxent use:
http://cran.r-project.org/web/packages/maxent/maxent.pdf
# LOAD LIBRARY
library(maxent)
# READ THE DATA, PREPARE THE CORPUS, and CREATE THE MATRIX
data <- read.csv(system.file("data/NYTimes.csv.gz",package="maxent"))
corpus <- Corpus(VectorSource(data$Title[1:150]))
matrix <- DocumentTermMatrix(corpus)
# TRAIN/PREDICT USING SPARSEM REPRESENTATION
sparse <- as.compressed.matrix(matrix)
model <- maxent(sparse[1:100,],data$Topic.Code[1:100])
results <- predict(model,sparse[101:150,])
Any idea how I can check the accuracy wrt the classification present in :
data$Topic.Code ?
I see the result is a 50:20 matrix but then how do I compare it with
data$Topic.Code.
Rgds,
Vineet
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