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Update spam_class_r.r #10

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11 changes: 8 additions & 3 deletions spam_class_r.r
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,10 @@ names <- read.csv("names.csv",header=FALSE,sep=";")
#Set the names of the dataset dataframe:
names(dataset) <- sapply((1:nrow(names)),function(i) toString(names[i,1]))

#Or there will be a "not a valid R variable name" error
dataset$y[dataset$y == 1] = "yes"
dataset$y[dataset$y == 0] = "no"

#make column y a factor variable for binary classification (spam or non-spam)
dataset$y <- as.factor(dataset$y)

Expand All @@ -19,6 +23,7 @@ sample <- dataset[sample(nrow(dataset), 1000),]

#Set up the packages:

#require(e1071) #better installed before sourcing
#install.packages(“caret”)

require(caret)
Expand All @@ -29,7 +34,7 @@ require(kernlab)

#install.packages(“doMC”)

require(doMC)
#require(doMC) #It is not valid from CRAN for R 3.3.2 Windows, but you may install it manually.


#Split the data in dataTrain and dataTest
Expand All @@ -38,7 +43,7 @@ dataTrain <- sample[ trainIndex,]
dataTest <- sample[-trainIndex,]

#set up multicore environment
registerDoMC(cores=5)
#registerDoMC(cores=5)


#Create the SVM model:
Expand All @@ -59,4 +64,4 @@ x <- train(y ~ .,
#Evaluate the model
pred <- predict(x,dataTest[,1:57])

acc <- confusionMatrix(pred,dataTest$y)
acc <- confusionMatrix(pred,dataTest$y)