Brunel - Computer Science - CS3002 Artificial Intelligence R Studio Scripts (ALL LABS Complete)
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Course
Computer Science (CS3002)
Institution
Brunel University (BU)
Compilation of the labs Intro to R, Classification, Clustering, Neural Networks Labs Scripts. CS3002 Artificial Intelligence Labs at Brunel University
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#decision trees
fit <- rpart(irisclassTrain~., method="class",data=irisvaluesTrain)
pfit<- prune(fit, cp=0.4)
plot(pfit, uniform=TRUE, main ="Decision Tree for iris data")
text(pfit, use.n=TRUE, all=TRUE, cex=1)
#decision trees different degrees
fit <- rpart(irisclassTrain~., method="class",data=irisvaluesTrain)
pfit<- prune(fit, cp=0.5)
plot(pfit, uniform=TRUE, main ="Decision Tree for iris data")
text(pfit, use.n=TRUE, all=TRUE, cex=1)
#test the classifer on the test set by calculating the predictions for each
testcase in our testset
treepred <- predict(pfit, irisvaluesTest, type = 'class')
n=length(irisclassTest) # the number of test cases
ncorrect = sum(treepred==irisclassTest) #number of correctly predicted
accuracy = ncorrect/n
print(accuracy)
#2 selected variables
plot(irisvaluesTest$width,irisvaluesTest$length, col = treepred)
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