Reading in the Data
QDA.A<-NULL
SVM.L.BO.A<-NULL
SVM.P.BO.A<-NULL
SVM.R.BO.A<-NULL
ArcLakeGroupSummary <- read_excel("~/Desktop/EPSRC Project /ArcLakeGroupSummary.xlsx")
dundeedata <- read_csv("~/Desktop/EPSRC Project /dundeedata.csv.xls")
colnames(dundeedata)[1]<-"GloboLakes_ID" # change the GloboLID column name to GloboLakes_ID to make the merge easier.
Data<-merge(ArcLakeGroupSummary, dundeedata, by = "GloboLakes_ID", all = TRUE )
Data<-subset(Data, Group!="NA") # The data set is back to the original 732 rows just with extra columns of information
Data$Group<-as.factor(Data$Group)
Data1<-data.frame(Data[,c("Group","PC1","PC2")])
# Stratify the entire training set into training and test sets
QDA
for(j in 1:500){
set.seed(j)
folds <- createFolds(y=factor(Data1$Group), k = 5, list = FALSE)
Data1$fold <- folds
# Using QDA to produce the CV error rate
CV.error<-NULL
for (i in 1:5) {
valid.data <- subset(Data1, fold == i)
train.data <- subset(Data1, fold != i)
qda.fit<-qda(formula = Group~PC1+PC2, data=train.data)
qda.y <- valid.data$Group
qda.predy<-predict(qda.fit, valid.data)$class
ith.test.error<- mean(qda.y!=qda.predy)
CV.error<-c(CV.error,(nrow(valid.data)/nrow(Data1))*ith.test.error)
}
QDA.A<-c(QDA.A, sum(CV.error))
}
QDA.A
## [1] 0.04371585 0.05054645 0.04644809 0.05191257 0.05054645 0.04918033
## [7] 0.04781421 0.04098361 0.05191257 0.04644809 0.04918033 0.05464481
## [13] 0.04781421 0.04918033 0.05327869 0.04644809 0.04781421 0.05327869
## [19] 0.04918033 0.04371585 0.04918033 0.04644809 0.04508197 0.04918033
## [25] 0.05054645 0.04781421 0.04508197 0.05054645 0.04644809 0.04918033
## [31] 0.04918033 0.05054645 0.05191257 0.04918033 0.04918033 0.04371585
## [37] 0.04918033 0.04644809 0.04781421 0.04508197 0.04918033 0.05327869
## [43] 0.05191257 0.05054645 0.04781421 0.05327869 0.04644809 0.04781421
## [49] 0.05054645 0.05327869 0.04371585 0.04918033 0.04781421 0.04098361
## [55] 0.04918033 0.05054645 0.05327869 0.04918033 0.04918033 0.05054645
## [61] 0.05327869 0.04098361 0.05191257 0.04781421 0.04781421 0.04781421
## [67] 0.04644809 0.05191257 0.04918033 0.04644809 0.04781421 0.04781421
## [73] 0.05327869 0.04781421 0.05191257 0.04918033 0.05054645 0.04918033
## [79] 0.05054645 0.04918033 0.04644809 0.04918033 0.04918033 0.04508197
## [85] 0.04918033 0.04918033 0.04918033 0.04644809 0.04781421 0.04234973
## [91] 0.04234973 0.04644809 0.04644809 0.04918033 0.04644809 0.05327869
## [97] 0.04918033 0.04781421 0.04918033 0.04781421 0.05191257 0.05054645
## [103] 0.04644809 0.04644809 0.04781421 0.05054645 0.04781421 0.05054645
## [109] 0.05327869 0.04508197 0.04644809 0.04644809 0.04918033 0.04781421
## [115] 0.05601093 0.04371585 0.04918033 0.04781421 0.04644809 0.03961749
## [121] 0.04918033 0.04781421 0.04918033 0.05327869 0.04644809 0.04918033
## [127] 0.05737705 0.04918033 0.05327869 0.05191257 0.04644809 0.05054645
## [133] 0.05191257 0.04508197 0.05054645 0.04371585 0.04508197 0.05054645
## [139] 0.04918033 0.05054645 0.04781421 0.04781421 0.04508197 0.05054645
## [145] 0.04781421 0.05327869 0.04781421 0.04781421 0.04644809 0.04918033
## [151] 0.05054645 0.04508197 0.04644809 0.05327869 0.04918033 0.04918033
## [157] 0.04371585 0.04918033 0.05191257 0.05054645 0.04781421 0.04508197
## [163] 0.04371585 0.04781421 0.04644809 0.05054645 0.04918033 0.04781421
## [169] 0.05191257 0.04918033 0.04644809 0.04918033 0.04508197 0.04644809
## [175] 0.05054645 0.05054645 0.05054645 0.04644809 0.05054645 0.05054645
## [181] 0.04508197 0.04508197 0.05054645 0.04508197 0.04234973 0.04508197
## [187] 0.05191257 0.04644809 0.05054645 0.04644809 0.04644809 0.04781421
## [193] 0.04508197 0.05327869 0.04781421 0.04918033 0.05327869 0.05054645
## [199] 0.04644809 0.05327869 0.04781421 0.05464481 0.04508197 0.05191257
## [205] 0.04781421 0.04644809 0.05327869 0.04644809 0.04371585 0.05327869
## [211] 0.04781421 0.04781421 0.04234973 0.04644809 0.04371585 0.04371585
## [217] 0.04644809 0.04918033 0.04781421 0.04918033 0.04508197 0.04234973
## [223] 0.04781421 0.04918033 0.05191257 0.04781421 0.04781421 0.05054645
## [229] 0.04234973 0.05054645 0.04644809 0.04371585 0.05874317 0.04781421
## [235] 0.05054645 0.04781421 0.04644809 0.04918033 0.05054645 0.04781421
## [241] 0.04234973 0.04918033 0.05327869 0.04781421 0.04508197 0.05054645
## [247] 0.04781421 0.04918033 0.04781421 0.05464481 0.04371585 0.04508197
## [253] 0.04644809 0.04918033 0.04644809 0.04644809 0.05191257 0.04508197
## [259] 0.04644809 0.04644809 0.04781421 0.04918033 0.04918033 0.04918033
## [265] 0.05191257 0.04644809 0.04644809 0.04781421 0.04508197 0.04918033
## [271] 0.04508197 0.04371585 0.04508197 0.04508197 0.05327869 0.04781421
## [277] 0.05191257 0.05464481 0.04644809 0.04918033 0.04918033 0.04644809
## [283] 0.04644809 0.04918033 0.04508197 0.04234973 0.04508197 0.04371585
## [289] 0.05874317 0.04644809 0.04918033 0.04918033 0.04918033 0.04781421
## [295] 0.04508197 0.04644809 0.04781421 0.04918033 0.04508197 0.04508197
## [301] 0.04234973 0.05601093 0.04781421 0.05327869 0.04371585 0.04644809
## [307] 0.04918033 0.04781421 0.04781421 0.04644809 0.04781421 0.04644809
## [313] 0.05054645 0.05191257 0.04918033 0.05191257 0.04918033 0.05327869
## [319] 0.04508197 0.05054645 0.04918033 0.04644809 0.05191257 0.04781421
## [325] 0.04644809 0.04644809 0.04781421 0.04918033 0.05191257 0.04371585
## [331] 0.04508197 0.05054645 0.05737705 0.05327869 0.04781421 0.04918033
## [337] 0.04508197 0.05054645 0.05327869 0.04918033 0.05054645 0.04781421
## [343] 0.05054645 0.05191257 0.04781421 0.05054645 0.04781421 0.05191257
## [349] 0.04371585 0.04644809 0.05054645 0.04918033 0.04918033 0.05191257
## [355] 0.05054645 0.04644809 0.04644809 0.04918033 0.05191257 0.04918033
## [361] 0.04508197 0.04781421 0.04918033 0.05191257 0.04644809 0.04781421
## [367] 0.04644809 0.04781421 0.04508197 0.04781421 0.05054645 0.05327869
## [373] 0.05054645 0.05191257 0.04644809 0.05054645 0.05054645 0.03961749
## [379] 0.04781421 0.05191257 0.04098361 0.04781421 0.05191257 0.04781421
## [385] 0.04781421 0.04918033 0.04644809 0.04918033 0.04644809 0.04781421
## [391] 0.04918033 0.04644809 0.04918033 0.05327869 0.04781421 0.04644809
## [397] 0.04234973 0.04508197 0.04781421 0.04918033 0.04644809 0.04508197
## [403] 0.05327869 0.04781421 0.04781421 0.04781421 0.04918033 0.05464481
## [409] 0.04508197 0.04508197 0.04918033 0.05054645 0.05054645 0.04781421
## [415] 0.04918033 0.04644809 0.04918033 0.05191257 0.04918033 0.04371585
## [421] 0.04781421 0.04918033 0.05191257 0.05191257 0.04918033 0.04781421
## [427] 0.04781421 0.04644809 0.04644809 0.04234973 0.04918033 0.05327869
## [433] 0.05054645 0.04781421 0.05191257 0.04371585 0.04508197 0.04644809
## [439] 0.05054645 0.05054645 0.04508197 0.04644809 0.04508197 0.04781421
## [445] 0.05054645 0.05327869 0.04918033 0.04644809 0.05054645 0.05054645
## [451] 0.04644809 0.04644809 0.04781421 0.05054645 0.04644809 0.05054645
## [457] 0.05191257 0.04918033 0.05054645 0.05191257 0.04918033 0.05054645
## [463] 0.05464481 0.04508197 0.04644809 0.04781421 0.05464481 0.04508197
## [469] 0.05054645 0.04644809 0.04918033 0.05054645 0.05054645 0.05054645
## [475] 0.04644809 0.04371585 0.04098361 0.04508197 0.04098361 0.04371585
## [481] 0.05054645 0.04508197 0.04098361 0.05191257 0.04508197 0.05327869
## [487] 0.04644809 0.04371585 0.04918033 0.04371585 0.04918033 0.04508197
## [493] 0.04918033 0.04918033 0.04781421 0.04508197 0.04644809 0.04918033
## [499] 0.05054645 0.04918033
SVM Linear BO
for(j in 1:500){
set.seed(j)
folds <- createFolds(y=factor(Data1$Group), k = 5, list = FALSE)
Data1$fold <- folds
# Using SVM linear kernel cost = 11173.88 - the best linear kernel SVM model considered.
CV.error<-NULL
for (i in 1:5) {
valid.data <- subset(Data1, fold == i)
train.data <- subset(Data1, fold != i)
svmfit<-svm(Group~PC1+PC2,data = train.data, kernel="linear", cost = 11173.88 ,scale=FALSE)
svm.y<-valid.data$Group
svm.predy<-predict(svmfit, valid.data)
ith.test.error<- mean(svm.y!=svm.predy)
CV.error<-c(CV.error,(nrow(valid.data)/nrow(Data1))*ith.test.error)
}
SVM.L.BO.A<-c(SVM.L.BO.A, sum(CV.error))
}
SVM.L.BO.A
## [1] 0.02459016 0.02595628 0.02185792 0.02459016 0.03142077 0.02049180
## [7] 0.02459016 0.02595628 0.02595628 0.02868852 0.03142077 0.02868852
## [13] 0.02185792 0.02049180 0.02185792 0.02322404 0.03005464 0.02595628
## [19] 0.02322404 0.02595628 0.02322404 0.02732240 0.02595628 0.02322404
## [25] 0.02595628 0.02732240 0.02595628 0.02459016 0.02185792 0.03142077
## [31] 0.02868852 0.03142077 0.02049180 0.03005464 0.02868852 0.02049180
## [37] 0.02732240 0.02595628 0.01775956 0.01639344 0.02049180 0.02322404
## [43] 0.02595628 0.02868852 0.02322404 0.02185792 0.03142077 0.03142077
## [49] 0.02595628 0.01912568 0.02595628 0.02049180 0.02322404 0.02459016
## [55] 0.02868852 0.03005464 0.02459016 0.02322404 0.03278689 0.02322404
## [61] 0.02049180 0.02595628 0.02459016 0.02868852 0.02049180 0.02732240
## [67] 0.02459016 0.02868852 0.03005464 0.02459016 0.02595628 0.03005464
## [73] 0.03142077 0.02322404 0.02185792 0.02459016 0.03278689 0.03415301
## [79] 0.03142077 0.02732240 0.02049180 0.02185792 0.02732240 0.02732240
## [85] 0.02322404 0.02595628 0.02322404 0.03142077 0.02049180 0.03142077
## [91] 0.02868852 0.02049180 0.03005464 0.02185792 0.02595628 0.02868852
## [97] 0.02732240 0.02459016 0.01912568 0.03278689 0.01912568 0.02185792
## [103] 0.02732240 0.02459016 0.03005464 0.03005464 0.02049180 0.02322404
## [109] 0.02868852 0.02732240 0.02459016 0.02595628 0.02868852 0.02595628
## [115] 0.02732240 0.02322404 0.03142077 0.02322404 0.02322404 0.02595628
## [121] 0.02732240 0.02459016 0.02322404 0.02732240 0.02049180 0.02732240
## [127] 0.02868852 0.02322404 0.03142077 0.02732240 0.02868852 0.02868852
## [133] 0.02595628 0.02595628 0.02732240 0.02049180 0.02459016 0.02595628
## [139] 0.01912568 0.03142077 0.02732240 0.02732240 0.02595628 0.02459016
## [145] 0.02322404 0.03142077 0.02049180 0.02185792 0.01912568 0.02322404
## [151] 0.02322404 0.02595628 0.02185792 0.02185792 0.02185792 0.02459016
## [157] 0.02595628 0.02595628 0.02595628 0.02732240 0.02049180 0.02049180
## [163] 0.02732240 0.02459016 0.02185792 0.02185792 0.02595628 0.02459016
## [169] 0.02322404 0.02732240 0.02459016 0.02732240 0.03142077 0.02595628
## [175] 0.02322404 0.03005464 0.02049180 0.02732240 0.02322404 0.02322404
## [181] 0.02049180 0.02049180 0.03142077 0.02595628 0.02868852 0.02322404
## [187] 0.02185792 0.02459016 0.02732240 0.02459016 0.02322404 0.02868852
## [193] 0.02185792 0.03415301 0.02459016 0.02595628 0.02732240 0.02732240
## [199] 0.02732240 0.03142077 0.02322404 0.03278689 0.02185792 0.03142077
## [205] 0.02732240 0.02049180 0.02595628 0.02322404 0.02322404 0.02732240
## [211] 0.02595628 0.02459016 0.01775956 0.02868852 0.02322404 0.02459016
## [217] 0.02459016 0.01912568 0.02595628 0.02185792 0.02732240 0.02322404
## [223] 0.03142077 0.02459016 0.02868852 0.02459016 0.02732240 0.03005464
## [229] 0.02732240 0.03278689 0.03005464 0.02322404 0.02049180 0.02732240
## [235] 0.01502732 0.02185792 0.02322404 0.02732240 0.03005464 0.02595628
## [241] 0.02185792 0.01912568 0.03142077 0.03278689 0.02868852 0.02732240
## [247] 0.02732240 0.02732240 0.03005464 0.03278689 0.02049180 0.02459016
## [253] 0.02459016 0.02732240 0.03005464 0.02732240 0.02459016 0.03005464
## [259] 0.02459016 0.03278689 0.02459016 0.02595628 0.02732240 0.02185792
## [265] 0.02049180 0.02732240 0.02322404 0.02732240 0.01912568 0.01775956
## [271] 0.02595628 0.02322404 0.02049180 0.02868852 0.03142077 0.02732240
## [277] 0.02595628 0.02322404 0.02322404 0.02185792 0.02459016 0.02459016
## [283] 0.02459016 0.02595628 0.02185792 0.02595628 0.02459016 0.02459016
## [289] 0.02868852 0.03142077 0.01775956 0.02459016 0.02049180 0.03005464
## [295] 0.02459016 0.02595628 0.02322404 0.02868852 0.02595628 0.02732240
## [301] 0.02322404 0.02322404 0.02322404 0.02595628 0.02868852 0.02459016
## [307] 0.02322404 0.02459016 0.02185792 0.02459016 0.02732240 0.02732240
## [313] 0.02595628 0.02459016 0.02049180 0.02595628 0.02459016 0.02322404
## [319] 0.02459016 0.02459016 0.02595628 0.02322404 0.01912568 0.02459016
## [325] 0.03142077 0.02459016 0.02732240 0.02732240 0.02595628 0.01639344
## [331] 0.01775956 0.02459016 0.02049180 0.02595628 0.03551913 0.02868852
## [337] 0.02322404 0.02868852 0.03142077 0.02595628 0.03142077 0.01639344
## [343] 0.02185792 0.02049180 0.02732240 0.02459016 0.02459016 0.02049180
## [349] 0.01912568 0.02595628 0.02049180 0.02185792 0.02322404 0.02732240
## [355] 0.02595628 0.02049180 0.02459016 0.01912568 0.03415301 0.02732240
## [361] 0.02185792 0.02595628 0.02732240 0.02322404 0.02868852 0.02322404
## [367] 0.02595628 0.02732240 0.02459016 0.02868852 0.02595628 0.02185792
## [373] 0.03278689 0.03005464 0.02595628 0.01912568 0.02459016 0.02595628
## [379] 0.02459016 0.02459016 0.02595628 0.03005464 0.02459016 0.02595628
## [385] 0.02322404 0.02185792 0.02868852 0.02595628 0.02459016 0.02185792
## [391] 0.02459016 0.02732240 0.01639344 0.02868852 0.02459016 0.03005464
## [397] 0.03005464 0.02049180 0.02459016 0.02868852 0.02595628 0.02322404
## [403] 0.02595628 0.02322404 0.03005464 0.02322404 0.02459016 0.03142077
## [409] 0.02868852 0.03142077 0.03142077 0.02595628 0.02595628 0.02322404
## [415] 0.01912568 0.02185792 0.02459016 0.02185792 0.02732240 0.02322404
## [421] 0.02459016 0.02459016 0.03005464 0.02322404 0.02868852 0.02322404
## [427] 0.02185792 0.02732240 0.03142077 0.02595628 0.02185792 0.02459016
## [433] 0.02185792 0.02459016 0.01912568 0.02049180 0.02049180 0.02459016
## [439] 0.02049180 0.02049180 0.02732240 0.02868852 0.02732240 0.02732240
## [445] 0.02459016 0.02595628 0.02868852 0.02185792 0.02322404 0.01912568
## [451] 0.03142077 0.02459016 0.02322404 0.02595628 0.02868852 0.02868852
## [457] 0.02322404 0.03005464 0.02732240 0.02868852 0.02322404 0.02732240
## [463] 0.02185792 0.02049180 0.02185792 0.02868852 0.03005464 0.02595628
## [469] 0.02595628 0.02322404 0.02868852 0.02322404 0.02595628 0.02459016
## [475] 0.02322404 0.02732240 0.01912568 0.02322404 0.02049180 0.02322404
## [481] 0.02595628 0.01775956 0.02322404 0.03142077 0.02732240 0.03551913
## [487] 0.02868852 0.02459016 0.02868852 0.02322404 0.02049180 0.02459016
## [493] 0.02185792 0.02595628 0.02595628 0.02049180 0.02185792 0.02732240
## [499] 0.02595628 0.11202186
SVM Polynomial BO
for(j in 1:500){
set.seed(j)
folds <- createFolds(y=factor(Data1$Group), k = 5, list = FALSE)
Data1$fold <- folds
# Using SVM linear kernel cost = 11173.88 - the best linear kernel SVM model considered.
CV.error<-NULL
for (i in 1:5) {
valid.data <- subset(Data1, fold == i)
train.data <- subset(Data1, fold != i)
svmfit<-svm(Group~PC1+PC2,data = train.data, kernel="polynomial", cost = 472.9585, degree = 1, gamma = 1 )
svm.y<-valid.data$Group
svm.predy<-predict(svmfit, valid.data)
ith.test.error<- mean(svm.y!=svm.predy)
CV.error<-c(CV.error,(nrow(valid.data)/nrow(Data1))*ith.test.error)
}
SVM.P.BO.A<-c(SVM.P.BO.A, sum(CV.error))
}
SVM.P.BO.A
## [1] 0.02459016 0.02322404 0.02185792 0.02459016 0.03142077 0.02459016
## [7] 0.02322404 0.02322404 0.02185792 0.01775956 0.02868852 0.02732240
## [13] 0.02185792 0.02185792 0.02185792 0.02459016 0.02459016 0.02732240
## [19] 0.02459016 0.02459016 0.02459016 0.02595628 0.02322404 0.02732240
## [25] 0.02732240 0.02049180 0.02732240 0.02185792 0.02049180 0.03005464
## [31] 0.02322404 0.02322404 0.02049180 0.02595628 0.03005464 0.02185792
## [37] 0.02185792 0.02459016 0.02185792 0.01912568 0.02459016 0.02459016
## [43] 0.02595628 0.03005464 0.02185792 0.02185792 0.02595628 0.03278689
## [49] 0.02459016 0.02732240 0.02732240 0.02049180 0.02459016 0.02322404
## [55] 0.02322404 0.02459016 0.02322404 0.02185792 0.02322404 0.02459016
## [61] 0.02732240 0.02322404 0.02322404 0.02732240 0.02459016 0.02322404
## [67] 0.02322404 0.02732240 0.02868852 0.02322404 0.02595628 0.02732240
## [73] 0.02868852 0.02322404 0.02049180 0.02459016 0.02459016 0.01912568
## [79] 0.02322404 0.02049180 0.02185792 0.02322404 0.02322404 0.02185792
## [85] 0.02322404 0.02459016 0.02322404 0.02732240 0.02185792 0.02595628
## [91] 0.02868852 0.02185792 0.02595628 0.02732240 0.02322404 0.02732240
## [97] 0.02322404 0.02185792 0.02049180 0.03005464 0.02185792 0.02595628
## [103] 0.02459016 0.02459016 0.02049180 0.02732240 0.02459016 0.02185792
## [109] 0.02459016 0.02049180 0.02322404 0.02868852 0.02185792 0.02322404
## [115] 0.02595628 0.02595628 0.02595628 0.02322404 0.02595628 0.02049180
## [121] 0.02322404 0.02185792 0.01912568 0.02459016 0.02185792 0.02732240
## [127] 0.02459016 0.02459016 0.03278689 0.02868852 0.02459016 0.03142077
## [133] 0.02868852 0.01775956 0.02322404 0.02049180 0.02322404 0.02868852
## [139] 0.02049180 0.02868852 0.02459016 0.02868852 0.02732240 0.02459016
## [145] 0.02868852 0.03005464 0.02049180 0.01912568 0.02459016 0.02732240
## [151] 0.02049180 0.02732240 0.02459016 0.01775956 0.01912568 0.02185792
## [157] 0.02322404 0.02595628 0.02459016 0.02868852 0.02459016 0.02185792
## [163] 0.02732240 0.02595628 0.02185792 0.02185792 0.02595628 0.02868852
## [169] 0.02732240 0.02732240 0.02049180 0.02322404 0.03551913 0.02459016
## [175] 0.02595628 0.02732240 0.02185792 0.02732240 0.02185792 0.02459016
## [181] 0.02049180 0.02185792 0.02459016 0.02049180 0.02459016 0.02322404
## [187] 0.01912568 0.02185792 0.02595628 0.02732240 0.02732240 0.03142077
## [193] 0.02049180 0.02732240 0.02732240 0.02459016 0.02459016 0.02868852
## [199] 0.02459016 0.02459016 0.02049180 0.03278689 0.02185792 0.03005464
## [205] 0.02049180 0.02459016 0.02459016 0.02322404 0.02322404 0.02459016
## [211] 0.02595628 0.02049180 0.01912568 0.02322404 0.02185792 0.02185792
## [217] 0.02595628 0.02459016 0.02322404 0.02459016 0.02732240 0.02868852
## [223] 0.03005464 0.02868852 0.02595628 0.02322404 0.02595628 0.02595628
## [229] 0.02459016 0.03142077 0.02868852 0.02049180 0.02185792 0.02459016
## [235] 0.02049180 0.02185792 0.02185792 0.02732240 0.02732240 0.02595628
## [241] 0.02459016 0.02049180 0.02595628 0.03551913 0.02732240 0.02459016
## [247] 0.02732240 0.02732240 0.02185792 0.03005464 0.02049180 0.02322404
## [253] 0.02459016 0.02732240 0.02868852 0.02185792 0.03005464 0.02185792
## [259] 0.02185792 0.02459016 0.02459016 0.02322404 0.02459016 0.02459016
## [265] 0.02732240 0.02732240 0.02595628 0.02868852 0.02322404 0.02185792
## [271] 0.02595628 0.02185792 0.02049180 0.02459016 0.03551913 0.02185792
## [277] 0.02049180 0.02732240 0.02322404 0.02459016 0.02732240 0.02322404
## [283] 0.02732240 0.02732240 0.02459016 0.01912568 0.02459016 0.02049180
## [289] 0.02732240 0.02732240 0.02049180 0.02185792 0.02185792 0.02185792
## [295] 0.02322404 0.02322404 0.02322404 0.02459016 0.02868852 0.02185792
## [301] 0.02185792 0.02185792 0.02595628 0.02732240 0.02595628 0.02185792
## [307] 0.02185792 0.02459016 0.02322404 0.02322404 0.01912568 0.02322404
## [313] 0.02049180 0.02185792 0.02185792 0.02595628 0.02185792 0.02595628
## [319] 0.02322404 0.02185792 0.02322404 0.02868852 0.02459016 0.02732240
## [325] 0.02322404 0.02732240 0.02459016 0.02459016 0.02595628 0.01912568
## [331] 0.02185792 0.01912568 0.02595628 0.02322404 0.02868852 0.02868852
## [337] 0.02185792 0.02322404 0.02868852 0.02322404 0.02322404 0.02185792
## [343] 0.02185792 0.02868852 0.03142077 0.02185792 0.02185792 0.02185792
## [349] 0.02322404 0.02322404 0.02185792 0.02322404 0.02322404 0.03005464
## [355] 0.02459016 0.02322404 0.02322404 0.01912568 0.02732240 0.02595628
## [361] 0.02049180 0.02459016 0.02595628 0.02322404 0.02868852 0.02459016
## [367] 0.02459016 0.02322404 0.02049180 0.03278689 0.01912568 0.02868852
## [373] 0.02459016 0.03005464 0.02595628 0.02732240 0.02459016 0.02322404
## [379] 0.03005464 0.02185792 0.02595628 0.02732240 0.02185792 0.02185792
## [385] 0.02322404 0.02322404 0.02868852 0.02868852 0.02049180 0.02322404
## [391] 0.02322404 0.02595628 0.02049180 0.02732240 0.02322404 0.02459016
## [397] 0.02732240 0.02322404 0.02049180 0.02459016 0.02185792 0.02459016
## [403] 0.02595628 0.02185792 0.02595628 0.02322404 0.02322404 0.03005464
## [409] 0.02322404 0.02595628 0.02595628 0.02595628 0.02322404 0.02595628
## [415] 0.02049180 0.02185792 0.01775956 0.02322404 0.02185792 0.02459016
## [421] 0.02459016 0.01912568 0.03278689 0.02185792 0.03005464 0.02595628
## [427] 0.02322404 0.02595628 0.02595628 0.02732240 0.02049180 0.02459016
## [433] 0.02732240 0.02732240 0.02185792 0.01775956 0.02322404 0.02595628
## [439] 0.02185792 0.02049180 0.02868852 0.02732240 0.02459016 0.02049180
## [445] 0.02459016 0.02732240 0.02459016 0.01639344 0.02732240 0.02322404
## [451] 0.02595628 0.02185792 0.02049180 0.02459016 0.02322404 0.02459016
## [457] 0.02595628 0.02459016 0.02459016 0.02868852 0.02459016 0.02732240
## [463] 0.02185792 0.02185792 0.01912568 0.02732240 0.02732240 0.02322404
## [469] 0.02595628 0.02459016 0.02732240 0.02732240 0.02185792 0.02322404
## [475] 0.02185792 0.02595628 0.02322404 0.02322404 0.02595628 0.02185792
## [481] 0.02459016 0.01639344 0.02322404 0.02459016 0.02868852 0.02185792
## [487] 0.02595628 0.02322404 0.02595628 0.02459016 0.02322404 0.01912568
## [493] 0.02049180 0.02459016 0.02459016 0.02185792 0.02595628 0.02185792
## [499] 0.02322404 0.02868852
SVM Radial BO
for(j in 1:500){
set.seed(j)
folds <- createFolds(y=factor(Data1$Group), k = 5, list = FALSE)
Data1$fold <- folds
# Using SVM linear kernel cost = 11173.88 - the best linear kernel SVM model considered.
CV.error<-NULL
for (i in 1:5) {
valid.data <- subset(Data1, fold == i)
train.data <- subset(Data1, fold != i)
svmfit<-svm(Group~PC1+PC2,data = train.data, kernel="radial", cost = 1538065, gamma = 0.02650774)
svm.y<-valid.data$Group
svm.predy<-predict(svmfit, valid.data)
ith.test.error<- mean(svm.y!=svm.predy)
CV.error<-c(CV.error,(nrow(valid.data)/nrow(Data1))*ith.test.error)
}
SVM.R.BO.A<-c(SVM.R.BO.A, sum(CV.error))
}
SVM.R.BO.A
## [1] 0.02322404 0.02459016 0.02049180 0.02732240 0.03825137 0.02322404
## [7] 0.02459016 0.02322404 0.02732240 0.02185792 0.02732240 0.03415301
## [13] 0.02049180 0.02049180 0.02868852 0.02732240 0.02185792 0.02185792
## [19] 0.02459016 0.02595628 0.02322404 0.02322404 0.02322404 0.02322404
## [25] 0.02459016 0.02459016 0.02322404 0.01912568 0.02049180 0.03005464
## [31] 0.02049180 0.02459016 0.02049180 0.01775956 0.03142077 0.01912568
## [37] 0.02185792 0.02322404 0.02049180 0.02459016 0.02459016 0.02595628
## [43] 0.02595628 0.02732240 0.02322404 0.02595628 0.03142077 0.03142077
## [49] 0.02732240 0.02732240 0.01912568 0.02322404 0.02459016 0.02049180
## [55] 0.02322404 0.02868852 0.02185792 0.02322404 0.03278689 0.02185792
## [61] 0.03005464 0.02322404 0.02595628 0.02595628 0.02049180 0.02185792
## [67] 0.02049180 0.02732240 0.03005464 0.02185792 0.01912568 0.02868852
## [73] 0.02459016 0.01912568 0.02185792 0.02459016 0.01775956 0.02732240
## [79] 0.03142077 0.02595628 0.02185792 0.02732240 0.02185792 0.03415301
## [85] 0.02185792 0.02595628 0.02322404 0.02459016 0.03005464 0.02459016
## [91] 0.02868852 0.03005464 0.02732240 0.02868852 0.02185792 0.02732240
## [97] 0.02185792 0.01912568 0.01775956 0.03278689 0.01912568 0.02868852
## [103] 0.02185792 0.03825137 0.02459016 0.02459016 0.02595628 0.01912568
## [109] 0.01775956 0.02185792 0.02185792 0.02868852 0.02868852 0.02322404
## [115] 0.02868852 0.02732240 0.02732240 0.02049180 0.02459016 0.02595628
## [121] 0.02595628 0.02732240 0.02049180 0.02732240 0.01775956 0.02732240
## [127] 0.03142077 0.02322404 0.03551913 0.02595628 0.03005464 0.02322404
## [133] 0.02595628 0.02185792 0.02459016 0.02049180 0.02595628 0.02322404
## [139] 0.02049180 0.02459016 0.02732240 0.02595628 0.02595628 0.02322404
## [145] 0.02185792 0.02732240 0.02185792 0.01366120 0.01912568 0.02868852
## [151] 0.03005464 0.02732240 0.03005464 0.01775956 0.02185792 0.02185792
## [157] 0.02049180 0.02732240 0.02868852 0.02459016 0.02595628 0.02459016
## [163] 0.02459016 0.02049180 0.02732240 0.02732240 0.02868852 0.03278689
## [169] 0.02459016 0.02732240 0.02595628 0.02185792 0.03825137 0.02459016
## [175] 0.02595628 0.02868852 0.02459016 0.02459016 0.02322404 0.02185792
## [181] 0.02185792 0.02322404 0.02595628 0.02049180 0.02459016 0.02322404
## [187] 0.02185792 0.02459016 0.02049180 0.02322404 0.02459016 0.02732240
## [193] 0.02049180 0.02868852 0.02868852 0.03005464 0.02185792 0.02595628
## [199] 0.02322404 0.02868852 0.02322404 0.03005464 0.02185792 0.03688525
## [205] 0.02595628 0.02185792 0.02185792 0.02185792 0.02185792 0.02732240
## [211] 0.02595628 0.02185792 0.02322404 0.02185792 0.01912568 0.02732240
## [217] 0.02322404 0.02322404 0.02459016 0.02185792 0.02732240 0.02732240
## [223] 0.02732240 0.02322404 0.02322404 0.01912568 0.02049180 0.02868852
## [229] 0.03005464 0.02322404 0.02868852 0.02049180 0.02595628 0.02459016
## [235] 0.01775956 0.02459016 0.02322404 0.03142077 0.02868852 0.02868852
## [241] 0.02732240 0.01775956 0.02732240 0.03688525 0.02459016 0.02868852
## [247] 0.03005464 0.03005464 0.02322404 0.02868852 0.01775956 0.01775956
## [253] 0.02868852 0.02459016 0.03005464 0.01775956 0.02322404 0.02459016
## [259] 0.02185792 0.03551913 0.02049180 0.02049180 0.02732240 0.02185792
## [265] 0.03005464 0.02595628 0.03005464 0.02868852 0.02049180 0.02185792
## [271] 0.02322404 0.03005464 0.02185792 0.02868852 0.03278689 0.02595628
## [277] 0.02185792 0.02868852 0.02868852 0.02595628 0.02595628 0.02732240
## [283] 0.02595628 0.03142077 0.01912568 0.01912568 0.02322404 0.02459016
## [289] 0.03005464 0.03005464 0.02322404 0.02049180 0.02459016 0.03005464
## [295] 0.02322404 0.02322404 0.02185792 0.02185792 0.02595628 0.03005464
## [301] 0.02049180 0.02595628 0.02459016 0.02322404 0.02868852 0.02049180
## [307] 0.02185792 0.02595628 0.02732240 0.02185792 0.01912568 0.02732240
## [313] 0.02185792 0.02732240 0.02322404 0.03142077 0.03142077 0.02459016
## [319] 0.02868852 0.03142077 0.02732240 0.02322404 0.01639344 0.02595628
## [325] 0.02459016 0.02595628 0.02595628 0.02459016 0.02595628 0.02322404
## [331] 0.03142077 0.02322404 0.02732240 0.02185792 0.02732240 0.03005464
## [337] 0.02595628 0.02322404 0.03278689 0.02322404 0.02459016 0.02185792
## [343] 0.02185792 0.02185792 0.02868852 0.01775956 0.02049180 0.02322404
## [349] 0.01775956 0.02185792 0.01775956 0.02049180 0.01912568 0.03005464
## [355] 0.02459016 0.02185792 0.02595628 0.02185792 0.02732240 0.02049180
## [361] 0.01775956 0.02732240 0.02595628 0.02185792 0.02732240 0.02185792
## [367] 0.02595628 0.03005464 0.02185792 0.03005464 0.02049180 0.03005464
## [373] 0.02595628 0.02322404 0.02322404 0.02322404 0.02049180 0.02868852
## [379] 0.02322404 0.02049180 0.02732240 0.02595628 0.02322404 0.02459016
## [385] 0.02595628 0.02459016 0.02459016 0.02868852 0.02049180 0.02049180
## [391] 0.02732240 0.02868852 0.02049180 0.02868852 0.02322404 0.02185792
## [397] 0.02595628 0.02732240 0.02322404 0.02322404 0.03278689 0.01775956
## [403] 0.03142077 0.02459016 0.02459016 0.02459016 0.02322404 0.02595628
## [409] 0.02459016 0.02185792 0.02459016 0.02732240 0.01775956 0.02322404
## [415] 0.02459016 0.02322404 0.02459016 0.02185792 0.02185792 0.02868852
## [421] 0.02459016 0.02322404 0.03278689 0.02049180 0.02732240 0.03005464
## [427] 0.02322404 0.02459016 0.02868852 0.03142077 0.02459016 0.02868852
## [433] 0.02868852 0.02322404 0.02459016 0.01912568 0.01912568 0.02049180
## [439] 0.02595628 0.02595628 0.02322404 0.03005464 0.02185792 0.02049180
## [445] 0.02868852 0.02595628 0.02322404 0.02185792 0.02868852 0.02459016
## [451] 0.02732240 0.02459016 0.02322404 0.02595628 0.02459016 0.02185792
## [457] 0.02459016 0.02322404 0.02185792 0.03278689 0.01912568 0.02595628
## [463] 0.01912568 0.02185792 0.02049180 0.02868852 0.02732240 0.02459016
## [469] 0.02185792 0.02185792 0.03142077 0.03005464 0.02459016 0.02185792
## [475] 0.02049180 0.02868852 0.01775956 0.02185792 0.01912568 0.02185792
## [481] 0.03142077 0.02049180 0.02322404 0.02732240 0.03142077 0.03278689
## [487] 0.02595628 0.02322404 0.03005464 0.02322404 0.02595628 0.02049180
## [493] 0.02049180 0.02732240 0.02185792 0.02049180 0.02322404 0.02732240
## [499] 0.02459016 0.02868852
Just the box plots I want.
QDA1<-data.frame(Classifier="QDA.", CV.Error.Rate=QDA.A)
QDA1$Classifier<-"QDA"
SVM.L.BO1<-data.frame(Classifier="SVM.L.BO.", CV.Error.Rate=SVM.L.BO.A)
SVM.L.BO1$Classifier<-"SVM Linear"
SVM.P.BO1<-data.frame(Classifier="SVM.P.BO.", CV.Error.Rate=SVM.P.BO.A)
SVM.P.BO1$Classifier<-"SVM Polynomial"
SVM.R.BO1<-data.frame(Classifier="SVM.R.BO.", CV.Error.Rate=SVM.R.BO.A)
SVM.R.BO1$Classifier<-"SVM Radial"
important.boxplots1<-rbind(QDA1, SVM.L.BO1, SVM.P.BO1, SVM.R.BO1)
important.boxplots1
## Classifier CV.Error.Rate
## 1 QDA 0.04371585
## 2 QDA 0.05054645
## 3 QDA 0.04644809
## 4 QDA 0.05191257
## 5 QDA 0.05054645
## 6 QDA 0.04918033
## 7 QDA 0.04781421
## 8 QDA 0.04098361
## 9 QDA 0.05191257
## 10 QDA 0.04644809
## 11 QDA 0.04918033
## 12 QDA 0.05464481
## 13 QDA 0.04781421
## 14 QDA 0.04918033
## 15 QDA 0.05327869
## 16 QDA 0.04644809
## 17 QDA 0.04781421
## 18 QDA 0.05327869
## 19 QDA 0.04918033
## 20 QDA 0.04371585
## 21 QDA 0.04918033
## 22 QDA 0.04644809
## 23 QDA 0.04508197
## 24 QDA 0.04918033
## 25 QDA 0.05054645
## 26 QDA 0.04781421
## 27 QDA 0.04508197
## 28 QDA 0.05054645
## 29 QDA 0.04644809
## 30 QDA 0.04918033
## 31 QDA 0.04918033
## 32 QDA 0.05054645
## 33 QDA 0.05191257
## 34 QDA 0.04918033
## 35 QDA 0.04918033
## 36 QDA 0.04371585
## 37 QDA 0.04918033
## 38 QDA 0.04644809
## 39 QDA 0.04781421
## 40 QDA 0.04508197
## 41 QDA 0.04918033
## 42 QDA 0.05327869
## 43 QDA 0.05191257
## 44 QDA 0.05054645
## 45 QDA 0.04781421
## 46 QDA 0.05327869
## 47 QDA 0.04644809
## 48 QDA 0.04781421
## 49 QDA 0.05054645
## 50 QDA 0.05327869
## 51 QDA 0.04371585
## 52 QDA 0.04918033
## 53 QDA 0.04781421
## 54 QDA 0.04098361
## 55 QDA 0.04918033
## 56 QDA 0.05054645
## 57 QDA 0.05327869
## 58 QDA 0.04918033
## 59 QDA 0.04918033
## 60 QDA 0.05054645
## 61 QDA 0.05327869
## 62 QDA 0.04098361
## 63 QDA 0.05191257
## 64 QDA 0.04781421
## 65 QDA 0.04781421
## 66 QDA 0.04781421
## 67 QDA 0.04644809
## 68 QDA 0.05191257
## 69 QDA 0.04918033
## 70 QDA 0.04644809
## 71 QDA 0.04781421
## 72 QDA 0.04781421
## 73 QDA 0.05327869
## 74 QDA 0.04781421
## 75 QDA 0.05191257
## 76 QDA 0.04918033
## 77 QDA 0.05054645
## 78 QDA 0.04918033
## 79 QDA 0.05054645
## 80 QDA 0.04918033
## 81 QDA 0.04644809
## 82 QDA 0.04918033
## 83 QDA 0.04918033
## 84 QDA 0.04508197
## 85 QDA 0.04918033
## 86 QDA 0.04918033
## 87 QDA 0.04918033
## 88 QDA 0.04644809
## 89 QDA 0.04781421
## 90 QDA 0.04234973
## 91 QDA 0.04234973
## 92 QDA 0.04644809
## 93 QDA 0.04644809
## 94 QDA 0.04918033
## 95 QDA 0.04644809
## 96 QDA 0.05327869
## 97 QDA 0.04918033
## 98 QDA 0.04781421
## 99 QDA 0.04918033
## 100 QDA 0.04781421
## 101 QDA 0.05191257
## 102 QDA 0.05054645
## 103 QDA 0.04644809
## 104 QDA 0.04644809
## 105 QDA 0.04781421
## 106 QDA 0.05054645
## 107 QDA 0.04781421
## 108 QDA 0.05054645
## 109 QDA 0.05327869
## 110 QDA 0.04508197
## 111 QDA 0.04644809
## 112 QDA 0.04644809
## 113 QDA 0.04918033
## 114 QDA 0.04781421
## 115 QDA 0.05601093
## 116 QDA 0.04371585
## 117 QDA 0.04918033
## 118 QDA 0.04781421
## 119 QDA 0.04644809
## 120 QDA 0.03961749
## 121 QDA 0.04918033
## 122 QDA 0.04781421
## 123 QDA 0.04918033
## 124 QDA 0.05327869
## 125 QDA 0.04644809
## 126 QDA 0.04918033
## 127 QDA 0.05737705
## 128 QDA 0.04918033
## 129 QDA 0.05327869
## 130 QDA 0.05191257
## 131 QDA 0.04644809
## 132 QDA 0.05054645
## 133 QDA 0.05191257
## 134 QDA 0.04508197
## 135 QDA 0.05054645
## 136 QDA 0.04371585
## 137 QDA 0.04508197
## 138 QDA 0.05054645
## 139 QDA 0.04918033
## 140 QDA 0.05054645
## 141 QDA 0.04781421
## 142 QDA 0.04781421
## 143 QDA 0.04508197
## 144 QDA 0.05054645
## 145 QDA 0.04781421
## 146 QDA 0.05327869
## 147 QDA 0.04781421
## 148 QDA 0.04781421
## 149 QDA 0.04644809
## 150 QDA 0.04918033
## 151 QDA 0.05054645
## 152 QDA 0.04508197
## 153 QDA 0.04644809
## 154 QDA 0.05327869
## 155 QDA 0.04918033
## 156 QDA 0.04918033
## 157 QDA 0.04371585
## 158 QDA 0.04918033
## 159 QDA 0.05191257
## 160 QDA 0.05054645
## 161 QDA 0.04781421
## 162 QDA 0.04508197
## 163 QDA 0.04371585
## 164 QDA 0.04781421
## 165 QDA 0.04644809
## 166 QDA 0.05054645
## 167 QDA 0.04918033
## 168 QDA 0.04781421
## 169 QDA 0.05191257
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## 523 SVM Linear 0.02595628
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## 528 SVM Linear 0.02459016
## 529 SVM Linear 0.02185792
## 530 SVM Linear 0.03142077
## 531 SVM Linear 0.02868852
## 532 SVM Linear 0.03142077
## 533 SVM Linear 0.02049180
## 534 SVM Linear 0.03005464
## 535 SVM Linear 0.02868852
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## 541 SVM Linear 0.02049180
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## 585 SVM Linear 0.02322404
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## 626 SVM Linear 0.02732240
## 627 SVM Linear 0.02868852
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## 629 SVM Linear 0.03142077
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## 658 SVM Linear 0.02595628
## 659 SVM Linear 0.02595628
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## 662 SVM Linear 0.02049180
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## 672 SVM Linear 0.02732240
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## 678 SVM Linear 0.02732240
## 679 SVM Linear 0.02322404
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## 682 SVM Linear 0.02049180
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## 699 SVM Linear 0.02732240
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## 705 SVM Linear 0.02732240
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## 709 SVM Linear 0.02322404
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## 716 SVM Linear 0.02459016
## 717 SVM Linear 0.02459016
## 718 SVM Linear 0.01912568
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## 722 SVM Linear 0.02322404
## 723 SVM Linear 0.03142077
## 724 SVM Linear 0.02459016
## 725 SVM Linear 0.02868852
## 726 SVM Linear 0.02459016
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## 732 SVM Linear 0.02322404
## 733 SVM Linear 0.02049180
## 734 SVM Linear 0.02732240
## 735 SVM Linear 0.01502732
## 736 SVM Linear 0.02185792
## 737 SVM Linear 0.02322404
## 738 SVM Linear 0.02732240
## 739 SVM Linear 0.03005464
## 740 SVM Linear 0.02595628
## 741 SVM Linear 0.02185792
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## 744 SVM Linear 0.03278689
## 745 SVM Linear 0.02868852
## 746 SVM Linear 0.02732240
## 747 SVM Linear 0.02732240
## 748 SVM Linear 0.02732240
## 749 SVM Linear 0.03005464
## 750 SVM Linear 0.03278689
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## 752 SVM Linear 0.02459016
## 753 SVM Linear 0.02459016
## 754 SVM Linear 0.02732240
## 755 SVM Linear 0.03005464
## 756 SVM Linear 0.02732240
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## 758 SVM Linear 0.03005464
## 759 SVM Linear 0.02459016
## 760 SVM Linear 0.03278689
## 761 SVM Linear 0.02459016
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## 765 SVM Linear 0.02049180
## 766 SVM Linear 0.02732240
## 767 SVM Linear 0.02322404
## 768 SVM Linear 0.02732240
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## 773 SVM Linear 0.02049180
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## 776 SVM Linear 0.02732240
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## 779 SVM Linear 0.02322404
## 780 SVM Linear 0.02185792
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## 782 SVM Linear 0.02459016
## 783 SVM Linear 0.02459016
## 784 SVM Linear 0.02595628
## 785 SVM Linear 0.02185792
## 786 SVM Linear 0.02595628
## 787 SVM Linear 0.02459016
## 788 SVM Linear 0.02459016
## 789 SVM Linear 0.02868852
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## 792 SVM Linear 0.02459016
## 793 SVM Linear 0.02049180
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## 795 SVM Linear 0.02459016
## 796 SVM Linear 0.02595628
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## 798 SVM Linear 0.02868852
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## 800 SVM Linear 0.02732240
## 801 SVM Linear 0.02322404
## 802 SVM Linear 0.02322404
## 803 SVM Linear 0.02322404
## 804 SVM Linear 0.02595628
## 805 SVM Linear 0.02868852
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## 807 SVM Linear 0.02322404
## 808 SVM Linear 0.02459016
## 809 SVM Linear 0.02185792
## 810 SVM Linear 0.02459016
## 811 SVM Linear 0.02732240
## 812 SVM Linear 0.02732240
## 813 SVM Linear 0.02595628
## 814 SVM Linear 0.02459016
## 815 SVM Linear 0.02049180
## 816 SVM Linear 0.02595628
## 817 SVM Linear 0.02459016
## 818 SVM Linear 0.02322404
## 819 SVM Linear 0.02459016
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## 822 SVM Linear 0.02322404
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## 826 SVM Linear 0.02459016
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## 838 SVM Linear 0.02868852
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## 841 SVM Linear 0.03142077
## 842 SVM Linear 0.01639344
## 843 SVM Linear 0.02185792
## 844 SVM Linear 0.02049180
## 845 SVM Linear 0.02732240
## 846 SVM Linear 0.02459016
## 847 SVM Linear 0.02459016
## 848 SVM Linear 0.02049180
## 849 SVM Linear 0.01912568
## 850 SVM Linear 0.02595628
## 851 SVM Linear 0.02049180
## 852 SVM Linear 0.02185792
## 853 SVM Linear 0.02322404
## 854 SVM Linear 0.02732240
## 855 SVM Linear 0.02595628
## 856 SVM Linear 0.02049180
## 857 SVM Linear 0.02459016
## 858 SVM Linear 0.01912568
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## 860 SVM Linear 0.02732240
## 861 SVM Linear 0.02185792
## 862 SVM Linear 0.02595628
## 863 SVM Linear 0.02732240
## 864 SVM Linear 0.02322404
## 865 SVM Linear 0.02868852
## 866 SVM Linear 0.02322404
## 867 SVM Linear 0.02595628
## 868 SVM Linear 0.02732240
## 869 SVM Linear 0.02459016
## 870 SVM Linear 0.02868852
## 871 SVM Linear 0.02595628
## 872 SVM Linear 0.02185792
## 873 SVM Linear 0.03278689
## 874 SVM Linear 0.03005464
## 875 SVM Linear 0.02595628
## 876 SVM Linear 0.01912568
## 877 SVM Linear 0.02459016
## 878 SVM Linear 0.02595628
## 879 SVM Linear 0.02459016
## 880 SVM Linear 0.02459016
## 881 SVM Linear 0.02595628
## 882 SVM Linear 0.03005464
## 883 SVM Linear 0.02459016
## 884 SVM Linear 0.02595628
## 885 SVM Linear 0.02322404
## 886 SVM Linear 0.02185792
## 887 SVM Linear 0.02868852
## 888 SVM Linear 0.02595628
## 889 SVM Linear 0.02459016
## 890 SVM Linear 0.02185792
## 891 SVM Linear 0.02459016
## 892 SVM Linear 0.02732240
## 893 SVM Linear 0.01639344
## 894 SVM Linear 0.02868852
## 895 SVM Linear 0.02459016
## 896 SVM Linear 0.03005464
## 897 SVM Linear 0.03005464
## 898 SVM Linear 0.02049180
## 899 SVM Linear 0.02459016
## 900 SVM Linear 0.02868852
## 901 SVM Linear 0.02595628
## 902 SVM Linear 0.02322404
## 903 SVM Linear 0.02595628
## 904 SVM Linear 0.02322404
## 905 SVM Linear 0.03005464
## 906 SVM Linear 0.02322404
## 907 SVM Linear 0.02459016
## 908 SVM Linear 0.03142077
## 909 SVM Linear 0.02868852
## 910 SVM Linear 0.03142077
## 911 SVM Linear 0.03142077
## 912 SVM Linear 0.02595628
## 913 SVM Linear 0.02595628
## 914 SVM Linear 0.02322404
## 915 SVM Linear 0.01912568
## 916 SVM Linear 0.02185792
## 917 SVM Linear 0.02459016
## 918 SVM Linear 0.02185792
## 919 SVM Linear 0.02732240
## 920 SVM Linear 0.02322404
## 921 SVM Linear 0.02459016
## 922 SVM Linear 0.02459016
## 923 SVM Linear 0.03005464
## 924 SVM Linear 0.02322404
## 925 SVM Linear 0.02868852
## 926 SVM Linear 0.02322404
## 927 SVM Linear 0.02185792
## 928 SVM Linear 0.02732240
## 929 SVM Linear 0.03142077
## 930 SVM Linear 0.02595628
## 931 SVM Linear 0.02185792
## 932 SVM Linear 0.02459016
## 933 SVM Linear 0.02185792
## 934 SVM Linear 0.02459016
## 935 SVM Linear 0.01912568
## 936 SVM Linear 0.02049180
## 937 SVM Linear 0.02049180
## 938 SVM Linear 0.02459016
## 939 SVM Linear 0.02049180
## 940 SVM Linear 0.02049180
## 941 SVM Linear 0.02732240
## 942 SVM Linear 0.02868852
## 943 SVM Linear 0.02732240
## 944 SVM Linear 0.02732240
## 945 SVM Linear 0.02459016
## 946 SVM Linear 0.02595628
## 947 SVM Linear 0.02868852
## 948 SVM Linear 0.02185792
## 949 SVM Linear 0.02322404
## 950 SVM Linear 0.01912568
## 951 SVM Linear 0.03142077
## 952 SVM Linear 0.02459016
## 953 SVM Linear 0.02322404
## 954 SVM Linear 0.02595628
## 955 SVM Linear 0.02868852
## 956 SVM Linear 0.02868852
## 957 SVM Linear 0.02322404
## 958 SVM Linear 0.03005464
## 959 SVM Linear 0.02732240
## 960 SVM Linear 0.02868852
## 961 SVM Linear 0.02322404
## 962 SVM Linear 0.02732240
## 963 SVM Linear 0.02185792
## 964 SVM Linear 0.02049180
## 965 SVM Linear 0.02185792
## 966 SVM Linear 0.02868852
## 967 SVM Linear 0.03005464
## 968 SVM Linear 0.02595628
## 969 SVM Linear 0.02595628
## 970 SVM Linear 0.02322404
## 971 SVM Linear 0.02868852
## 972 SVM Linear 0.02322404
## 973 SVM Linear 0.02595628
## 974 SVM Linear 0.02459016
## 975 SVM Linear 0.02322404
## 976 SVM Linear 0.02732240
## 977 SVM Linear 0.01912568
## 978 SVM Linear 0.02322404
## 979 SVM Linear 0.02049180
## 980 SVM Linear 0.02322404
## 981 SVM Linear 0.02595628
## 982 SVM Linear 0.01775956
## 983 SVM Linear 0.02322404
## 984 SVM Linear 0.03142077
## 985 SVM Linear 0.02732240
## 986 SVM Linear 0.03551913
## 987 SVM Linear 0.02868852
## 988 SVM Linear 0.02459016
## 989 SVM Linear 0.02868852
## 990 SVM Linear 0.02322404
## 991 SVM Linear 0.02049180
## 992 SVM Linear 0.02459016
## 993 SVM Linear 0.02185792
## 994 SVM Linear 0.02595628
## 995 SVM Linear 0.02595628
## 996 SVM Linear 0.02049180
## 997 SVM Linear 0.02185792
## 998 SVM Linear 0.02732240
## 999 SVM Linear 0.02595628
## 1000 SVM Linear 0.11202186
## 1001 SVM Polynomial 0.02459016
## 1002 SVM Polynomial 0.02322404
## 1003 SVM Polynomial 0.02185792
## 1004 SVM Polynomial 0.02459016
## 1005 SVM Polynomial 0.03142077
## 1006 SVM Polynomial 0.02459016
## 1007 SVM Polynomial 0.02322404
## 1008 SVM Polynomial 0.02322404
## 1009 SVM Polynomial 0.02185792
## 1010 SVM Polynomial 0.01775956
## 1011 SVM Polynomial 0.02868852
## 1012 SVM Polynomial 0.02732240
## 1013 SVM Polynomial 0.02185792
## 1014 SVM Polynomial 0.02185792
## 1015 SVM Polynomial 0.02185792
## 1016 SVM Polynomial 0.02459016
## 1017 SVM Polynomial 0.02459016
## 1018 SVM Polynomial 0.02732240
## 1019 SVM Polynomial 0.02459016
## 1020 SVM Polynomial 0.02459016
## 1021 SVM Polynomial 0.02459016
## 1022 SVM Polynomial 0.02595628
## 1023 SVM Polynomial 0.02322404
## 1024 SVM Polynomial 0.02732240
## 1025 SVM Polynomial 0.02732240
## 1026 SVM Polynomial 0.02049180
## 1027 SVM Polynomial 0.02732240
## 1028 SVM Polynomial 0.02185792
## 1029 SVM Polynomial 0.02049180
## 1030 SVM Polynomial 0.03005464
## 1031 SVM Polynomial 0.02322404
## 1032 SVM Polynomial 0.02322404
## 1033 SVM Polynomial 0.02049180
## 1034 SVM Polynomial 0.02595628
## 1035 SVM Polynomial 0.03005464
## 1036 SVM Polynomial 0.02185792
## 1037 SVM Polynomial 0.02185792
## 1038 SVM Polynomial 0.02459016
## 1039 SVM Polynomial 0.02185792
## 1040 SVM Polynomial 0.01912568
## 1041 SVM Polynomial 0.02459016
## 1042 SVM Polynomial 0.02459016
## 1043 SVM Polynomial 0.02595628
## 1044 SVM Polynomial 0.03005464
## 1045 SVM Polynomial 0.02185792
## 1046 SVM Polynomial 0.02185792
## 1047 SVM Polynomial 0.02595628
## 1048 SVM Polynomial 0.03278689
## 1049 SVM Polynomial 0.02459016
## 1050 SVM Polynomial 0.02732240
## 1051 SVM Polynomial 0.02732240
## 1052 SVM Polynomial 0.02049180
## 1053 SVM Polynomial 0.02459016
## 1054 SVM Polynomial 0.02322404
## 1055 SVM Polynomial 0.02322404
## 1056 SVM Polynomial 0.02459016
## 1057 SVM Polynomial 0.02322404
## 1058 SVM Polynomial 0.02185792
## 1059 SVM Polynomial 0.02322404
## 1060 SVM Polynomial 0.02459016
## 1061 SVM Polynomial 0.02732240
## 1062 SVM Polynomial 0.02322404
## 1063 SVM Polynomial 0.02322404
## 1064 SVM Polynomial 0.02732240
## 1065 SVM Polynomial 0.02459016
## 1066 SVM Polynomial 0.02322404
## 1067 SVM Polynomial 0.02322404
## 1068 SVM Polynomial 0.02732240
## 1069 SVM Polynomial 0.02868852
## 1070 SVM Polynomial 0.02322404
## 1071 SVM Polynomial 0.02595628
## 1072 SVM Polynomial 0.02732240
## 1073 SVM Polynomial 0.02868852
## 1074 SVM Polynomial 0.02322404
## 1075 SVM Polynomial 0.02049180
## 1076 SVM Polynomial 0.02459016
## 1077 SVM Polynomial 0.02459016
## 1078 SVM Polynomial 0.01912568
## 1079 SVM Polynomial 0.02322404
## 1080 SVM Polynomial 0.02049180
## 1081 SVM Polynomial 0.02185792
## 1082 SVM Polynomial 0.02322404
## 1083 SVM Polynomial 0.02322404
## 1084 SVM Polynomial 0.02185792
## 1085 SVM Polynomial 0.02322404
## 1086 SVM Polynomial 0.02459016
## 1087 SVM Polynomial 0.02322404
## 1088 SVM Polynomial 0.02732240
## 1089 SVM Polynomial 0.02185792
## 1090 SVM Polynomial 0.02595628
## 1091 SVM Polynomial 0.02868852
## 1092 SVM Polynomial 0.02185792
## 1093 SVM Polynomial 0.02595628
## 1094 SVM Polynomial 0.02732240
## 1095 SVM Polynomial 0.02322404
## 1096 SVM Polynomial 0.02732240
## 1097 SVM Polynomial 0.02322404
## 1098 SVM Polynomial 0.02185792
## 1099 SVM Polynomial 0.02049180
## 1100 SVM Polynomial 0.03005464
## 1101 SVM Polynomial 0.02185792
## 1102 SVM Polynomial 0.02595628
## 1103 SVM Polynomial 0.02459016
## 1104 SVM Polynomial 0.02459016
## 1105 SVM Polynomial 0.02049180
## 1106 SVM Polynomial 0.02732240
## 1107 SVM Polynomial 0.02459016
## 1108 SVM Polynomial 0.02185792
## 1109 SVM Polynomial 0.02459016
## 1110 SVM Polynomial 0.02049180
## 1111 SVM Polynomial 0.02322404
## 1112 SVM Polynomial 0.02868852
## 1113 SVM Polynomial 0.02185792
## 1114 SVM Polynomial 0.02322404
## 1115 SVM Polynomial 0.02595628
## 1116 SVM Polynomial 0.02595628
## 1117 SVM Polynomial 0.02595628
## 1118 SVM Polynomial 0.02322404
## 1119 SVM Polynomial 0.02595628
## 1120 SVM Polynomial 0.02049180
## 1121 SVM Polynomial 0.02322404
## 1122 SVM Polynomial 0.02185792
## 1123 SVM Polynomial 0.01912568
## 1124 SVM Polynomial 0.02459016
## 1125 SVM Polynomial 0.02185792
## 1126 SVM Polynomial 0.02732240
## 1127 SVM Polynomial 0.02459016
## 1128 SVM Polynomial 0.02459016
## 1129 SVM Polynomial 0.03278689
## 1130 SVM Polynomial 0.02868852
## 1131 SVM Polynomial 0.02459016
## 1132 SVM Polynomial 0.03142077
## 1133 SVM Polynomial 0.02868852
## 1134 SVM Polynomial 0.01775956
## 1135 SVM Polynomial 0.02322404
## 1136 SVM Polynomial 0.02049180
## 1137 SVM Polynomial 0.02322404
## 1138 SVM Polynomial 0.02868852
## 1139 SVM Polynomial 0.02049180
## 1140 SVM Polynomial 0.02868852
## 1141 SVM Polynomial 0.02459016
## 1142 SVM Polynomial 0.02868852
## 1143 SVM Polynomial 0.02732240
## 1144 SVM Polynomial 0.02459016
## 1145 SVM Polynomial 0.02868852
## 1146 SVM Polynomial 0.03005464
## 1147 SVM Polynomial 0.02049180
## 1148 SVM Polynomial 0.01912568
## 1149 SVM Polynomial 0.02459016
## 1150 SVM Polynomial 0.02732240
## 1151 SVM Polynomial 0.02049180
## 1152 SVM Polynomial 0.02732240
## 1153 SVM Polynomial 0.02459016
## 1154 SVM Polynomial 0.01775956
## 1155 SVM Polynomial 0.01912568
## 1156 SVM Polynomial 0.02185792
## 1157 SVM Polynomial 0.02322404
## 1158 SVM Polynomial 0.02595628
## 1159 SVM Polynomial 0.02459016
## 1160 SVM Polynomial 0.02868852
## 1161 SVM Polynomial 0.02459016
## 1162 SVM Polynomial 0.02185792
## 1163 SVM Polynomial 0.02732240
## 1164 SVM Polynomial 0.02595628
## 1165 SVM Polynomial 0.02185792
## 1166 SVM Polynomial 0.02185792
## 1167 SVM Polynomial 0.02595628
## 1168 SVM Polynomial 0.02868852
## 1169 SVM Polynomial 0.02732240
## 1170 SVM Polynomial 0.02732240
## 1171 SVM Polynomial 0.02049180
## 1172 SVM Polynomial 0.02322404
## 1173 SVM Polynomial 0.03551913
## 1174 SVM Polynomial 0.02459016
## 1175 SVM Polynomial 0.02595628
## 1176 SVM Polynomial 0.02732240
## 1177 SVM Polynomial 0.02185792
## 1178 SVM Polynomial 0.02732240
## 1179 SVM Polynomial 0.02185792
## 1180 SVM Polynomial 0.02459016
## 1181 SVM Polynomial 0.02049180
## 1182 SVM Polynomial 0.02185792
## 1183 SVM Polynomial 0.02459016
## 1184 SVM Polynomial 0.02049180
## 1185 SVM Polynomial 0.02459016
## 1186 SVM Polynomial 0.02322404
## 1187 SVM Polynomial 0.01912568
## 1188 SVM Polynomial 0.02185792
## 1189 SVM Polynomial 0.02595628
## 1190 SVM Polynomial 0.02732240
## 1191 SVM Polynomial 0.02732240
## 1192 SVM Polynomial 0.03142077
## 1193 SVM Polynomial 0.02049180
## 1194 SVM Polynomial 0.02732240
## 1195 SVM Polynomial 0.02732240
## 1196 SVM Polynomial 0.02459016
## 1197 SVM Polynomial 0.02459016
## 1198 SVM Polynomial 0.02868852
## 1199 SVM Polynomial 0.02459016
## 1200 SVM Polynomial 0.02459016
## 1201 SVM Polynomial 0.02049180
## 1202 SVM Polynomial 0.03278689
## 1203 SVM Polynomial 0.02185792
## 1204 SVM Polynomial 0.03005464
## 1205 SVM Polynomial 0.02049180
## 1206 SVM Polynomial 0.02459016
## 1207 SVM Polynomial 0.02459016
## 1208 SVM Polynomial 0.02322404
## 1209 SVM Polynomial 0.02322404
## 1210 SVM Polynomial 0.02459016
## 1211 SVM Polynomial 0.02595628
## 1212 SVM Polynomial 0.02049180
## 1213 SVM Polynomial 0.01912568
## 1214 SVM Polynomial 0.02322404
## 1215 SVM Polynomial 0.02185792
## 1216 SVM Polynomial 0.02185792
## 1217 SVM Polynomial 0.02595628
## 1218 SVM Polynomial 0.02459016
## 1219 SVM Polynomial 0.02322404
## 1220 SVM Polynomial 0.02459016
## 1221 SVM Polynomial 0.02732240
## 1222 SVM Polynomial 0.02868852
## 1223 SVM Polynomial 0.03005464
## 1224 SVM Polynomial 0.02868852
## 1225 SVM Polynomial 0.02595628
## 1226 SVM Polynomial 0.02322404
## 1227 SVM Polynomial 0.02595628
## 1228 SVM Polynomial 0.02595628
## 1229 SVM Polynomial 0.02459016
## 1230 SVM Polynomial 0.03142077
## 1231 SVM Polynomial 0.02868852
## 1232 SVM Polynomial 0.02049180
## 1233 SVM Polynomial 0.02185792
## 1234 SVM Polynomial 0.02459016
## 1235 SVM Polynomial 0.02049180
## 1236 SVM Polynomial 0.02185792
## 1237 SVM Polynomial 0.02185792
## 1238 SVM Polynomial 0.02732240
## 1239 SVM Polynomial 0.02732240
## 1240 SVM Polynomial 0.02595628
## 1241 SVM Polynomial 0.02459016
## 1242 SVM Polynomial 0.02049180
## 1243 SVM Polynomial 0.02595628
## 1244 SVM Polynomial 0.03551913
## 1245 SVM Polynomial 0.02732240
## 1246 SVM Polynomial 0.02459016
## 1247 SVM Polynomial 0.02732240
## 1248 SVM Polynomial 0.02732240
## 1249 SVM Polynomial 0.02185792
## 1250 SVM Polynomial 0.03005464
## 1251 SVM Polynomial 0.02049180
## 1252 SVM Polynomial 0.02322404
## 1253 SVM Polynomial 0.02459016
## 1254 SVM Polynomial 0.02732240
## 1255 SVM Polynomial 0.02868852
## 1256 SVM Polynomial 0.02185792
## 1257 SVM Polynomial 0.03005464
## 1258 SVM Polynomial 0.02185792
## 1259 SVM Polynomial 0.02185792
## 1260 SVM Polynomial 0.02459016
## 1261 SVM Polynomial 0.02459016
## 1262 SVM Polynomial 0.02322404
## 1263 SVM Polynomial 0.02459016
## 1264 SVM Polynomial 0.02459016
## 1265 SVM Polynomial 0.02732240
## 1266 SVM Polynomial 0.02732240
## 1267 SVM Polynomial 0.02595628
## 1268 SVM Polynomial 0.02868852
## 1269 SVM Polynomial 0.02322404
## 1270 SVM Polynomial 0.02185792
## 1271 SVM Polynomial 0.02595628
## 1272 SVM Polynomial 0.02185792
## 1273 SVM Polynomial 0.02049180
## 1274 SVM Polynomial 0.02459016
## 1275 SVM Polynomial 0.03551913
## 1276 SVM Polynomial 0.02185792
## 1277 SVM Polynomial 0.02049180
## 1278 SVM Polynomial 0.02732240
## 1279 SVM Polynomial 0.02322404
## 1280 SVM Polynomial 0.02459016
## 1281 SVM Polynomial 0.02732240
## 1282 SVM Polynomial 0.02322404
## 1283 SVM Polynomial 0.02732240
## 1284 SVM Polynomial 0.02732240
## 1285 SVM Polynomial 0.02459016
## 1286 SVM Polynomial 0.01912568
## 1287 SVM Polynomial 0.02459016
## 1288 SVM Polynomial 0.02049180
## 1289 SVM Polynomial 0.02732240
## 1290 SVM Polynomial 0.02732240
## 1291 SVM Polynomial 0.02049180
## 1292 SVM Polynomial 0.02185792
## 1293 SVM Polynomial 0.02185792
## 1294 SVM Polynomial 0.02185792
## 1295 SVM Polynomial 0.02322404
## 1296 SVM Polynomial 0.02322404
## 1297 SVM Polynomial 0.02322404
## 1298 SVM Polynomial 0.02459016
## 1299 SVM Polynomial 0.02868852
## 1300 SVM Polynomial 0.02185792
## 1301 SVM Polynomial 0.02185792
## 1302 SVM Polynomial 0.02185792
## 1303 SVM Polynomial 0.02595628
## 1304 SVM Polynomial 0.02732240
## 1305 SVM Polynomial 0.02595628
## 1306 SVM Polynomial 0.02185792
## 1307 SVM Polynomial 0.02185792
## 1308 SVM Polynomial 0.02459016
## 1309 SVM Polynomial 0.02322404
## 1310 SVM Polynomial 0.02322404
## 1311 SVM Polynomial 0.01912568
## 1312 SVM Polynomial 0.02322404
## 1313 SVM Polynomial 0.02049180
## 1314 SVM Polynomial 0.02185792
## 1315 SVM Polynomial 0.02185792
## 1316 SVM Polynomial 0.02595628
## 1317 SVM Polynomial 0.02185792
## 1318 SVM Polynomial 0.02595628
## 1319 SVM Polynomial 0.02322404
## 1320 SVM Polynomial 0.02185792
## 1321 SVM Polynomial 0.02322404
## 1322 SVM Polynomial 0.02868852
## 1323 SVM Polynomial 0.02459016
## 1324 SVM Polynomial 0.02732240
## 1325 SVM Polynomial 0.02322404
## 1326 SVM Polynomial 0.02732240
## 1327 SVM Polynomial 0.02459016
## 1328 SVM Polynomial 0.02459016
## 1329 SVM Polynomial 0.02595628
## 1330 SVM Polynomial 0.01912568
## 1331 SVM Polynomial 0.02185792
## 1332 SVM Polynomial 0.01912568
## 1333 SVM Polynomial 0.02595628
## 1334 SVM Polynomial 0.02322404
## 1335 SVM Polynomial 0.02868852
## 1336 SVM Polynomial 0.02868852
## 1337 SVM Polynomial 0.02185792
## 1338 SVM Polynomial 0.02322404
## 1339 SVM Polynomial 0.02868852
## 1340 SVM Polynomial 0.02322404
## 1341 SVM Polynomial 0.02322404
## 1342 SVM Polynomial 0.02185792
## 1343 SVM Polynomial 0.02185792
## 1344 SVM Polynomial 0.02868852
## 1345 SVM Polynomial 0.03142077
## 1346 SVM Polynomial 0.02185792
## 1347 SVM Polynomial 0.02185792
## 1348 SVM Polynomial 0.02185792
## 1349 SVM Polynomial 0.02322404
## 1350 SVM Polynomial 0.02322404
## 1351 SVM Polynomial 0.02185792
## 1352 SVM Polynomial 0.02322404
## 1353 SVM Polynomial 0.02322404
## 1354 SVM Polynomial 0.03005464
## 1355 SVM Polynomial 0.02459016
## 1356 SVM Polynomial 0.02322404
## 1357 SVM Polynomial 0.02322404
## 1358 SVM Polynomial 0.01912568
## 1359 SVM Polynomial 0.02732240
## 1360 SVM Polynomial 0.02595628
## 1361 SVM Polynomial 0.02049180
## 1362 SVM Polynomial 0.02459016
## 1363 SVM Polynomial 0.02595628
## 1364 SVM Polynomial 0.02322404
## 1365 SVM Polynomial 0.02868852
## 1366 SVM Polynomial 0.02459016
## 1367 SVM Polynomial 0.02459016
## 1368 SVM Polynomial 0.02322404
## 1369 SVM Polynomial 0.02049180
## 1370 SVM Polynomial 0.03278689
## 1371 SVM Polynomial 0.01912568
## 1372 SVM Polynomial 0.02868852
## 1373 SVM Polynomial 0.02459016
## 1374 SVM Polynomial 0.03005464
## 1375 SVM Polynomial 0.02595628
## 1376 SVM Polynomial 0.02732240
## 1377 SVM Polynomial 0.02459016
## 1378 SVM Polynomial 0.02322404
## 1379 SVM Polynomial 0.03005464
## 1380 SVM Polynomial 0.02185792
## 1381 SVM Polynomial 0.02595628
## 1382 SVM Polynomial 0.02732240
## 1383 SVM Polynomial 0.02185792
## 1384 SVM Polynomial 0.02185792
## 1385 SVM Polynomial 0.02322404
## 1386 SVM Polynomial 0.02322404
## 1387 SVM Polynomial 0.02868852
## 1388 SVM Polynomial 0.02868852
## 1389 SVM Polynomial 0.02049180
## 1390 SVM Polynomial 0.02322404
## 1391 SVM Polynomial 0.02322404
## 1392 SVM Polynomial 0.02595628
## 1393 SVM Polynomial 0.02049180
## 1394 SVM Polynomial 0.02732240
## 1395 SVM Polynomial 0.02322404
## 1396 SVM Polynomial 0.02459016
## 1397 SVM Polynomial 0.02732240
## 1398 SVM Polynomial 0.02322404
## 1399 SVM Polynomial 0.02049180
## 1400 SVM Polynomial 0.02459016
## 1401 SVM Polynomial 0.02185792
## 1402 SVM Polynomial 0.02459016
## 1403 SVM Polynomial 0.02595628
## 1404 SVM Polynomial 0.02185792
## 1405 SVM Polynomial 0.02595628
## 1406 SVM Polynomial 0.02322404
## 1407 SVM Polynomial 0.02322404
## 1408 SVM Polynomial 0.03005464
## 1409 SVM Polynomial 0.02322404
## 1410 SVM Polynomial 0.02595628
## 1411 SVM Polynomial 0.02595628
## 1412 SVM Polynomial 0.02595628
## 1413 SVM Polynomial 0.02322404
## 1414 SVM Polynomial 0.02595628
## 1415 SVM Polynomial 0.02049180
## 1416 SVM Polynomial 0.02185792
## 1417 SVM Polynomial 0.01775956
## 1418 SVM Polynomial 0.02322404
## 1419 SVM Polynomial 0.02185792
## 1420 SVM Polynomial 0.02459016
## 1421 SVM Polynomial 0.02459016
## 1422 SVM Polynomial 0.01912568
## 1423 SVM Polynomial 0.03278689
## 1424 SVM Polynomial 0.02185792
## 1425 SVM Polynomial 0.03005464
## 1426 SVM Polynomial 0.02595628
## 1427 SVM Polynomial 0.02322404
## 1428 SVM Polynomial 0.02595628
## 1429 SVM Polynomial 0.02595628
## 1430 SVM Polynomial 0.02732240
## 1431 SVM Polynomial 0.02049180
## 1432 SVM Polynomial 0.02459016
## 1433 SVM Polynomial 0.02732240
## 1434 SVM Polynomial 0.02732240
## 1435 SVM Polynomial 0.02185792
## 1436 SVM Polynomial 0.01775956
## 1437 SVM Polynomial 0.02322404
## 1438 SVM Polynomial 0.02595628
## 1439 SVM Polynomial 0.02185792
## 1440 SVM Polynomial 0.02049180
## 1441 SVM Polynomial 0.02868852
## 1442 SVM Polynomial 0.02732240
## 1443 SVM Polynomial 0.02459016
## 1444 SVM Polynomial 0.02049180
## 1445 SVM Polynomial 0.02459016
## 1446 SVM Polynomial 0.02732240
## 1447 SVM Polynomial 0.02459016
## 1448 SVM Polynomial 0.01639344
## 1449 SVM Polynomial 0.02732240
## 1450 SVM Polynomial 0.02322404
## 1451 SVM Polynomial 0.02595628
## 1452 SVM Polynomial 0.02185792
## 1453 SVM Polynomial 0.02049180
## 1454 SVM Polynomial 0.02459016
## 1455 SVM Polynomial 0.02322404
## 1456 SVM Polynomial 0.02459016
## 1457 SVM Polynomial 0.02595628
## 1458 SVM Polynomial 0.02459016
## 1459 SVM Polynomial 0.02459016
## 1460 SVM Polynomial 0.02868852
## 1461 SVM Polynomial 0.02459016
## 1462 SVM Polynomial 0.02732240
## 1463 SVM Polynomial 0.02185792
## 1464 SVM Polynomial 0.02185792
## 1465 SVM Polynomial 0.01912568
## 1466 SVM Polynomial 0.02732240
## 1467 SVM Polynomial 0.02732240
## 1468 SVM Polynomial 0.02322404
## 1469 SVM Polynomial 0.02595628
## 1470 SVM Polynomial 0.02459016
## 1471 SVM Polynomial 0.02732240
## 1472 SVM Polynomial 0.02732240
## 1473 SVM Polynomial 0.02185792
## 1474 SVM Polynomial 0.02322404
## 1475 SVM Polynomial 0.02185792
## 1476 SVM Polynomial 0.02595628
## 1477 SVM Polynomial 0.02322404
## 1478 SVM Polynomial 0.02322404
## 1479 SVM Polynomial 0.02595628
## 1480 SVM Polynomial 0.02185792
## 1481 SVM Polynomial 0.02459016
## 1482 SVM Polynomial 0.01639344
## 1483 SVM Polynomial 0.02322404
## 1484 SVM Polynomial 0.02459016
## 1485 SVM Polynomial 0.02868852
## 1486 SVM Polynomial 0.02185792
## 1487 SVM Polynomial 0.02595628
## 1488 SVM Polynomial 0.02322404
## 1489 SVM Polynomial 0.02595628
## 1490 SVM Polynomial 0.02459016
## 1491 SVM Polynomial 0.02322404
## 1492 SVM Polynomial 0.01912568
## 1493 SVM Polynomial 0.02049180
## 1494 SVM Polynomial 0.02459016
## 1495 SVM Polynomial 0.02459016
## 1496 SVM Polynomial 0.02185792
## 1497 SVM Polynomial 0.02595628
## 1498 SVM Polynomial 0.02185792
## 1499 SVM Polynomial 0.02322404
## 1500 SVM Polynomial 0.02868852
## 1501 SVM Radial 0.02322404
## 1502 SVM Radial 0.02459016
## 1503 SVM Radial 0.02049180
## 1504 SVM Radial 0.02732240
## 1505 SVM Radial 0.03825137
## 1506 SVM Radial 0.02322404
## 1507 SVM Radial 0.02459016
## 1508 SVM Radial 0.02322404
## 1509 SVM Radial 0.02732240
## 1510 SVM Radial 0.02185792
## 1511 SVM Radial 0.02732240
## 1512 SVM Radial 0.03415301
## 1513 SVM Radial 0.02049180
## 1514 SVM Radial 0.02049180
## 1515 SVM Radial 0.02868852
## 1516 SVM Radial 0.02732240
## 1517 SVM Radial 0.02185792
## 1518 SVM Radial 0.02185792
## 1519 SVM Radial 0.02459016
## 1520 SVM Radial 0.02595628
## 1521 SVM Radial 0.02322404
## 1522 SVM Radial 0.02322404
## 1523 SVM Radial 0.02322404
## 1524 SVM Radial 0.02322404
## 1525 SVM Radial 0.02459016
## 1526 SVM Radial 0.02459016
## 1527 SVM Radial 0.02322404
## 1528 SVM Radial 0.01912568
## 1529 SVM Radial 0.02049180
## 1530 SVM Radial 0.03005464
## 1531 SVM Radial 0.02049180
## 1532 SVM Radial 0.02459016
## 1533 SVM Radial 0.02049180
## 1534 SVM Radial 0.01775956
## 1535 SVM Radial 0.03142077
## 1536 SVM Radial 0.01912568
## 1537 SVM Radial 0.02185792
## 1538 SVM Radial 0.02322404
## 1539 SVM Radial 0.02049180
## 1540 SVM Radial 0.02459016
## 1541 SVM Radial 0.02459016
## 1542 SVM Radial 0.02595628
## 1543 SVM Radial 0.02595628
## 1544 SVM Radial 0.02732240
## 1545 SVM Radial 0.02322404
## 1546 SVM Radial 0.02595628
## 1547 SVM Radial 0.03142077
## 1548 SVM Radial 0.03142077
## 1549 SVM Radial 0.02732240
## 1550 SVM Radial 0.02732240
## 1551 SVM Radial 0.01912568
## 1552 SVM Radial 0.02322404
## 1553 SVM Radial 0.02459016
## 1554 SVM Radial 0.02049180
## 1555 SVM Radial 0.02322404
## 1556 SVM Radial 0.02868852
## 1557 SVM Radial 0.02185792
## 1558 SVM Radial 0.02322404
## 1559 SVM Radial 0.03278689
## 1560 SVM Radial 0.02185792
## 1561 SVM Radial 0.03005464
## 1562 SVM Radial 0.02322404
## 1563 SVM Radial 0.02595628
## 1564 SVM Radial 0.02595628
## 1565 SVM Radial 0.02049180
## 1566 SVM Radial 0.02185792
## 1567 SVM Radial 0.02049180
## 1568 SVM Radial 0.02732240
## 1569 SVM Radial 0.03005464
## 1570 SVM Radial 0.02185792
## 1571 SVM Radial 0.01912568
## 1572 SVM Radial 0.02868852
## 1573 SVM Radial 0.02459016
## 1574 SVM Radial 0.01912568
## 1575 SVM Radial 0.02185792
## 1576 SVM Radial 0.02459016
## 1577 SVM Radial 0.01775956
## 1578 SVM Radial 0.02732240
## 1579 SVM Radial 0.03142077
## 1580 SVM Radial 0.02595628
## 1581 SVM Radial 0.02185792
## 1582 SVM Radial 0.02732240
## 1583 SVM Radial 0.02185792
## 1584 SVM Radial 0.03415301
## 1585 SVM Radial 0.02185792
## 1586 SVM Radial 0.02595628
## 1587 SVM Radial 0.02322404
## 1588 SVM Radial 0.02459016
## 1589 SVM Radial 0.03005464
## 1590 SVM Radial 0.02459016
## 1591 SVM Radial 0.02868852
## 1592 SVM Radial 0.03005464
## 1593 SVM Radial 0.02732240
## 1594 SVM Radial 0.02868852
## 1595 SVM Radial 0.02185792
## 1596 SVM Radial 0.02732240
## 1597 SVM Radial 0.02185792
## 1598 SVM Radial 0.01912568
## 1599 SVM Radial 0.01775956
## 1600 SVM Radial 0.03278689
## 1601 SVM Radial 0.01912568
## 1602 SVM Radial 0.02868852
## 1603 SVM Radial 0.02185792
## 1604 SVM Radial 0.03825137
## 1605 SVM Radial 0.02459016
## 1606 SVM Radial 0.02459016
## 1607 SVM Radial 0.02595628
## 1608 SVM Radial 0.01912568
## 1609 SVM Radial 0.01775956
## 1610 SVM Radial 0.02185792
## 1611 SVM Radial 0.02185792
## 1612 SVM Radial 0.02868852
## 1613 SVM Radial 0.02868852
## 1614 SVM Radial 0.02322404
## 1615 SVM Radial 0.02868852
## 1616 SVM Radial 0.02732240
## 1617 SVM Radial 0.02732240
## 1618 SVM Radial 0.02049180
## 1619 SVM Radial 0.02459016
## 1620 SVM Radial 0.02595628
## 1621 SVM Radial 0.02595628
## 1622 SVM Radial 0.02732240
## 1623 SVM Radial 0.02049180
## 1624 SVM Radial 0.02732240
## 1625 SVM Radial 0.01775956
## 1626 SVM Radial 0.02732240
## 1627 SVM Radial 0.03142077
## 1628 SVM Radial 0.02322404
## 1629 SVM Radial 0.03551913
## 1630 SVM Radial 0.02595628
## 1631 SVM Radial 0.03005464
## 1632 SVM Radial 0.02322404
## 1633 SVM Radial 0.02595628
## 1634 SVM Radial 0.02185792
## 1635 SVM Radial 0.02459016
## 1636 SVM Radial 0.02049180
## 1637 SVM Radial 0.02595628
## 1638 SVM Radial 0.02322404
## 1639 SVM Radial 0.02049180
## 1640 SVM Radial 0.02459016
## 1641 SVM Radial 0.02732240
## 1642 SVM Radial 0.02595628
## 1643 SVM Radial 0.02595628
## 1644 SVM Radial 0.02322404
## 1645 SVM Radial 0.02185792
## 1646 SVM Radial 0.02732240
## 1647 SVM Radial 0.02185792
## 1648 SVM Radial 0.01366120
## 1649 SVM Radial 0.01912568
## 1650 SVM Radial 0.02868852
## 1651 SVM Radial 0.03005464
## 1652 SVM Radial 0.02732240
## 1653 SVM Radial 0.03005464
## 1654 SVM Radial 0.01775956
## 1655 SVM Radial 0.02185792
## 1656 SVM Radial 0.02185792
## 1657 SVM Radial 0.02049180
## 1658 SVM Radial 0.02732240
## 1659 SVM Radial 0.02868852
## 1660 SVM Radial 0.02459016
## 1661 SVM Radial 0.02595628
## 1662 SVM Radial 0.02459016
## 1663 SVM Radial 0.02459016
## 1664 SVM Radial 0.02049180
## 1665 SVM Radial 0.02732240
## 1666 SVM Radial 0.02732240
## 1667 SVM Radial 0.02868852
## 1668 SVM Radial 0.03278689
## 1669 SVM Radial 0.02459016
## 1670 SVM Radial 0.02732240
## 1671 SVM Radial 0.02595628
## 1672 SVM Radial 0.02185792
## 1673 SVM Radial 0.03825137
## 1674 SVM Radial 0.02459016
## 1675 SVM Radial 0.02595628
## 1676 SVM Radial 0.02868852
## 1677 SVM Radial 0.02459016
## 1678 SVM Radial 0.02459016
## 1679 SVM Radial 0.02322404
## 1680 SVM Radial 0.02185792
## 1681 SVM Radial 0.02185792
## 1682 SVM Radial 0.02322404
## 1683 SVM Radial 0.02595628
## 1684 SVM Radial 0.02049180
## 1685 SVM Radial 0.02459016
## 1686 SVM Radial 0.02322404
## 1687 SVM Radial 0.02185792
## 1688 SVM Radial 0.02459016
## 1689 SVM Radial 0.02049180
## 1690 SVM Radial 0.02322404
## 1691 SVM Radial 0.02459016
## 1692 SVM Radial 0.02732240
## 1693 SVM Radial 0.02049180
## 1694 SVM Radial 0.02868852
## 1695 SVM Radial 0.02868852
## 1696 SVM Radial 0.03005464
## 1697 SVM Radial 0.02185792
## 1698 SVM Radial 0.02595628
## 1699 SVM Radial 0.02322404
## 1700 SVM Radial 0.02868852
## 1701 SVM Radial 0.02322404
## 1702 SVM Radial 0.03005464
## 1703 SVM Radial 0.02185792
## 1704 SVM Radial 0.03688525
## 1705 SVM Radial 0.02595628
## 1706 SVM Radial 0.02185792
## 1707 SVM Radial 0.02185792
## 1708 SVM Radial 0.02185792
## 1709 SVM Radial 0.02185792
## 1710 SVM Radial 0.02732240
## 1711 SVM Radial 0.02595628
## 1712 SVM Radial 0.02185792
## 1713 SVM Radial 0.02322404
## 1714 SVM Radial 0.02185792
## 1715 SVM Radial 0.01912568
## 1716 SVM Radial 0.02732240
## 1717 SVM Radial 0.02322404
## 1718 SVM Radial 0.02322404
## 1719 SVM Radial 0.02459016
## 1720 SVM Radial 0.02185792
## 1721 SVM Radial 0.02732240
## 1722 SVM Radial 0.02732240
## 1723 SVM Radial 0.02732240
## 1724 SVM Radial 0.02322404
## 1725 SVM Radial 0.02322404
## 1726 SVM Radial 0.01912568
## 1727 SVM Radial 0.02049180
## 1728 SVM Radial 0.02868852
## 1729 SVM Radial 0.03005464
## 1730 SVM Radial 0.02322404
## 1731 SVM Radial 0.02868852
## 1732 SVM Radial 0.02049180
## 1733 SVM Radial 0.02595628
## 1734 SVM Radial 0.02459016
## 1735 SVM Radial 0.01775956
## 1736 SVM Radial 0.02459016
## 1737 SVM Radial 0.02322404
## 1738 SVM Radial 0.03142077
## 1739 SVM Radial 0.02868852
## 1740 SVM Radial 0.02868852
## 1741 SVM Radial 0.02732240
## 1742 SVM Radial 0.01775956
## 1743 SVM Radial 0.02732240
## 1744 SVM Radial 0.03688525
## 1745 SVM Radial 0.02459016
## 1746 SVM Radial 0.02868852
## 1747 SVM Radial 0.03005464
## 1748 SVM Radial 0.03005464
## 1749 SVM Radial 0.02322404
## 1750 SVM Radial 0.02868852
## 1751 SVM Radial 0.01775956
## 1752 SVM Radial 0.01775956
## 1753 SVM Radial 0.02868852
## 1754 SVM Radial 0.02459016
## 1755 SVM Radial 0.03005464
## 1756 SVM Radial 0.01775956
## 1757 SVM Radial 0.02322404
## 1758 SVM Radial 0.02459016
## 1759 SVM Radial 0.02185792
## 1760 SVM Radial 0.03551913
## 1761 SVM Radial 0.02049180
## 1762 SVM Radial 0.02049180
## 1763 SVM Radial 0.02732240
## 1764 SVM Radial 0.02185792
## 1765 SVM Radial 0.03005464
## 1766 SVM Radial 0.02595628
## 1767 SVM Radial 0.03005464
## 1768 SVM Radial 0.02868852
## 1769 SVM Radial 0.02049180
## 1770 SVM Radial 0.02185792
## 1771 SVM Radial 0.02322404
## 1772 SVM Radial 0.03005464
## 1773 SVM Radial 0.02185792
## 1774 SVM Radial 0.02868852
## 1775 SVM Radial 0.03278689
## 1776 SVM Radial 0.02595628
## 1777 SVM Radial 0.02185792
## 1778 SVM Radial 0.02868852
## 1779 SVM Radial 0.02868852
## 1780 SVM Radial 0.02595628
## 1781 SVM Radial 0.02595628
## 1782 SVM Radial 0.02732240
## 1783 SVM Radial 0.02595628
## 1784 SVM Radial 0.03142077
## 1785 SVM Radial 0.01912568
## 1786 SVM Radial 0.01912568
## 1787 SVM Radial 0.02322404
## 1788 SVM Radial 0.02459016
## 1789 SVM Radial 0.03005464
## 1790 SVM Radial 0.03005464
## 1791 SVM Radial 0.02322404
## 1792 SVM Radial 0.02049180
## 1793 SVM Radial 0.02459016
## 1794 SVM Radial 0.03005464
## 1795 SVM Radial 0.02322404
## 1796 SVM Radial 0.02322404
## 1797 SVM Radial 0.02185792
## 1798 SVM Radial 0.02185792
## 1799 SVM Radial 0.02595628
## 1800 SVM Radial 0.03005464
## 1801 SVM Radial 0.02049180
## 1802 SVM Radial 0.02595628
## 1803 SVM Radial 0.02459016
## 1804 SVM Radial 0.02322404
## 1805 SVM Radial 0.02868852
## 1806 SVM Radial 0.02049180
## 1807 SVM Radial 0.02185792
## 1808 SVM Radial 0.02595628
## 1809 SVM Radial 0.02732240
## 1810 SVM Radial 0.02185792
## 1811 SVM Radial 0.01912568
## 1812 SVM Radial 0.02732240
## 1813 SVM Radial 0.02185792
## 1814 SVM Radial 0.02732240
## 1815 SVM Radial 0.02322404
## 1816 SVM Radial 0.03142077
## 1817 SVM Radial 0.03142077
## 1818 SVM Radial 0.02459016
## 1819 SVM Radial 0.02868852
## 1820 SVM Radial 0.03142077
## 1821 SVM Radial 0.02732240
## 1822 SVM Radial 0.02322404
## 1823 SVM Radial 0.01639344
## 1824 SVM Radial 0.02595628
## 1825 SVM Radial 0.02459016
## 1826 SVM Radial 0.02595628
## 1827 SVM Radial 0.02595628
## 1828 SVM Radial 0.02459016
## 1829 SVM Radial 0.02595628
## 1830 SVM Radial 0.02322404
## 1831 SVM Radial 0.03142077
## 1832 SVM Radial 0.02322404
## 1833 SVM Radial 0.02732240
## 1834 SVM Radial 0.02185792
## 1835 SVM Radial 0.02732240
## 1836 SVM Radial 0.03005464
## 1837 SVM Radial 0.02595628
## 1838 SVM Radial 0.02322404
## 1839 SVM Radial 0.03278689
## 1840 SVM Radial 0.02322404
## 1841 SVM Radial 0.02459016
## 1842 SVM Radial 0.02185792
## 1843 SVM Radial 0.02185792
## 1844 SVM Radial 0.02185792
## 1845 SVM Radial 0.02868852
## 1846 SVM Radial 0.01775956
## 1847 SVM Radial 0.02049180
## 1848 SVM Radial 0.02322404
## 1849 SVM Radial 0.01775956
## 1850 SVM Radial 0.02185792
## 1851 SVM Radial 0.01775956
## 1852 SVM Radial 0.02049180
## 1853 SVM Radial 0.01912568
## 1854 SVM Radial 0.03005464
## 1855 SVM Radial 0.02459016
## 1856 SVM Radial 0.02185792
## 1857 SVM Radial 0.02595628
## 1858 SVM Radial 0.02185792
## 1859 SVM Radial 0.02732240
## 1860 SVM Radial 0.02049180
## 1861 SVM Radial 0.01775956
## 1862 SVM Radial 0.02732240
## 1863 SVM Radial 0.02595628
## 1864 SVM Radial 0.02185792
## 1865 SVM Radial 0.02732240
## 1866 SVM Radial 0.02185792
## 1867 SVM Radial 0.02595628
## 1868 SVM Radial 0.03005464
## 1869 SVM Radial 0.02185792
## 1870 SVM Radial 0.03005464
## 1871 SVM Radial 0.02049180
## 1872 SVM Radial 0.03005464
## 1873 SVM Radial 0.02595628
## 1874 SVM Radial 0.02322404
## 1875 SVM Radial 0.02322404
## 1876 SVM Radial 0.02322404
## 1877 SVM Radial 0.02049180
## 1878 SVM Radial 0.02868852
## 1879 SVM Radial 0.02322404
## 1880 SVM Radial 0.02049180
## 1881 SVM Radial 0.02732240
## 1882 SVM Radial 0.02595628
## 1883 SVM Radial 0.02322404
## 1884 SVM Radial 0.02459016
## 1885 SVM Radial 0.02595628
## 1886 SVM Radial 0.02459016
## 1887 SVM Radial 0.02459016
## 1888 SVM Radial 0.02868852
## 1889 SVM Radial 0.02049180
## 1890 SVM Radial 0.02049180
## 1891 SVM Radial 0.02732240
## 1892 SVM Radial 0.02868852
## 1893 SVM Radial 0.02049180
## 1894 SVM Radial 0.02868852
## 1895 SVM Radial 0.02322404
## 1896 SVM Radial 0.02185792
## 1897 SVM Radial 0.02595628
## 1898 SVM Radial 0.02732240
## 1899 SVM Radial 0.02322404
## 1900 SVM Radial 0.02322404
## 1901 SVM Radial 0.03278689
## 1902 SVM Radial 0.01775956
## 1903 SVM Radial 0.03142077
## 1904 SVM Radial 0.02459016
## 1905 SVM Radial 0.02459016
## 1906 SVM Radial 0.02459016
## 1907 SVM Radial 0.02322404
## 1908 SVM Radial 0.02595628
## 1909 SVM Radial 0.02459016
## 1910 SVM Radial 0.02185792
## 1911 SVM Radial 0.02459016
## 1912 SVM Radial 0.02732240
## 1913 SVM Radial 0.01775956
## 1914 SVM Radial 0.02322404
## 1915 SVM Radial 0.02459016
## 1916 SVM Radial 0.02322404
## 1917 SVM Radial 0.02459016
## 1918 SVM Radial 0.02185792
## 1919 SVM Radial 0.02185792
## 1920 SVM Radial 0.02868852
## 1921 SVM Radial 0.02459016
## 1922 SVM Radial 0.02322404
## 1923 SVM Radial 0.03278689
## 1924 SVM Radial 0.02049180
## 1925 SVM Radial 0.02732240
## 1926 SVM Radial 0.03005464
## 1927 SVM Radial 0.02322404
## 1928 SVM Radial 0.02459016
## 1929 SVM Radial 0.02868852
## 1930 SVM Radial 0.03142077
## 1931 SVM Radial 0.02459016
## 1932 SVM Radial 0.02868852
## 1933 SVM Radial 0.02868852
## 1934 SVM Radial 0.02322404
## 1935 SVM Radial 0.02459016
## 1936 SVM Radial 0.01912568
## 1937 SVM Radial 0.01912568
## 1938 SVM Radial 0.02049180
## 1939 SVM Radial 0.02595628
## 1940 SVM Radial 0.02595628
## 1941 SVM Radial 0.02322404
## 1942 SVM Radial 0.03005464
## 1943 SVM Radial 0.02185792
## 1944 SVM Radial 0.02049180
## 1945 SVM Radial 0.02868852
## 1946 SVM Radial 0.02595628
## 1947 SVM Radial 0.02322404
## 1948 SVM Radial 0.02185792
## 1949 SVM Radial 0.02868852
## 1950 SVM Radial 0.02459016
## 1951 SVM Radial 0.02732240
## 1952 SVM Radial 0.02459016
## 1953 SVM Radial 0.02322404
## 1954 SVM Radial 0.02595628
## 1955 SVM Radial 0.02459016
## 1956 SVM Radial 0.02185792
## 1957 SVM Radial 0.02459016
## 1958 SVM Radial 0.02322404
## 1959 SVM Radial 0.02185792
## 1960 SVM Radial 0.03278689
## 1961 SVM Radial 0.01912568
## 1962 SVM Radial 0.02595628
## 1963 SVM Radial 0.01912568
## 1964 SVM Radial 0.02185792
## 1965 SVM Radial 0.02049180
## 1966 SVM Radial 0.02868852
## 1967 SVM Radial 0.02732240
## 1968 SVM Radial 0.02459016
## 1969 SVM Radial 0.02185792
## 1970 SVM Radial 0.02185792
## 1971 SVM Radial 0.03142077
## 1972 SVM Radial 0.03005464
## 1973 SVM Radial 0.02459016
## 1974 SVM Radial 0.02185792
## 1975 SVM Radial 0.02049180
## 1976 SVM Radial 0.02868852
## 1977 SVM Radial 0.01775956
## 1978 SVM Radial 0.02185792
## 1979 SVM Radial 0.01912568
## 1980 SVM Radial 0.02185792
## 1981 SVM Radial 0.03142077
## 1982 SVM Radial 0.02049180
## 1983 SVM Radial 0.02322404
## 1984 SVM Radial 0.02732240
## 1985 SVM Radial 0.03142077
## 1986 SVM Radial 0.03278689
## 1987 SVM Radial 0.02595628
## 1988 SVM Radial 0.02322404
## 1989 SVM Radial 0.03005464
## 1990 SVM Radial 0.02322404
## 1991 SVM Radial 0.02595628
## 1992 SVM Radial 0.02049180
## 1993 SVM Radial 0.02049180
## 1994 SVM Radial 0.02732240
## 1995 SVM Radial 0.02185792
## 1996 SVM Radial 0.02049180
## 1997 SVM Radial 0.02322404
## 1998 SVM Radial 0.02732240
## 1999 SVM Radial 0.02459016
## 2000 SVM Radial 0.02868852
four1<-ggplot(important.boxplots1, aes(x=Classifier, y=CV.Error.Rate))+geom_boxplot(color = "green")+geom_jitter(alpha=0.1) + ylab("Cross-Validation Error Rate")
four1
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.03962 0.04645 0.04781 0.04836 0.05055 0.05874
quantile(QDA.A, probs=c(0.025, 0.975))
## 2.5% 97.5%
## 0.04234973 0.05399590
## [1] 0.00305645
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.01503 0.02322 0.02459 0.02551 0.02732 0.11200
quantile(SVM.L.BO.A , probs=c(0.025, 0.975))
## 2.5% 97.5%
## 0.01912568 0.03278689
## [1] 0.005309149
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.01639 0.02186 0.02459 0.02442 0.02596 0.03552
quantile(SVM.P.BO.A , probs=c(0.025, 0.975))
## 2.5% 97.5%
## 0.01912568 0.03077186
## [1] 0.003088413
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.01366 0.02186 0.02459 0.02484 0.02732 0.03825
quantile(SVM.R.BO.A , probs=c(0.025, 0.975))
## 2.5% 97.5%
## 0.01775956 0.03278689
## [1] 0.00394055