Displaying 3 results from an estimated 3 matches for "misclassifc".
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misclassify
2009 May 12
1
questions on rpart (tree changes when rearrange the order of covariates?!)
...(PimaIndiansDiabetes2)
mydata<-PimaIndiansDiabetes2
library(rpart)
fit2<-rpart(diabetes~., data=mydata,method="class")
plot(fit2,uniform=T,main="CART for original data")
text(fit2,use.n=T,cex=0.6)
printcp(fit2)
table(predict(fit2,type="class"),mydata$diabetes)
## misclassifcation table: rows are fitted class
neg pos
neg 437 68
pos 63 200
#Klimt(fit2,mydata)
pmydata<-data.frame(mydata[,c(1,6,3,4,5,2,7,8,9)])
fit3<-rpart(diabetes~., data=pmydata,method="class")
plot(fit3,uniform=T,main="CART after exchaging mass & glucose")
text...
2009 May 22
1
bug in rpart?
...(PimaIndiansDiabetes2)
mydata<-PimaIndiansDiabetes2
library(rpart)
fit2<-rpart(diabetes~., data=mydata,method="class")
plot(fit2,uniform=T,main="CART for original data")
text(fit2,use.n=T,cex=0.6)
printcp(fit2)
table(predict(fit2,type="class"),mydata$diabetes)
## misclassifcation table: rows are fitted class
neg pos
neg 437 68
pos 63 200
pmydata<-data.frame(mydata[,c(1,6,3,4,5,2,7,8,9)])
fit3<-rpart(diabetes~., data=pmydata,method="class")
plot(fit3,uniform=T,main="CART after exchaging mass & glucose")
text(fit3,use.n=T,cex=0...
2005 Aug 05
1
Statistical significance of a classifier
Hi,
I have a bunch of data points x from two classes A & B, and I'm creating
a classifier. So I have a function f(x) which estimates the probability
that x is in class A. (I have an equal number of examples of each, so
p(class) = 0.5.)
One way of seeing how well this does is to compute the error rate on the
test set, i.e. if f(x)>0.5 call it A, and see how many times I