Re: [R] cross validation using e1071:SVM
thank you so much for your help. if i am not wrong then createDataPartition can be used to create stratified random splits of a data set. is there other way to do that? Thank you -- View this message in context: http://r.789695.n4.nabble.com/cross-validation-using-e1071-SVM-tp3055335p3057684.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] cross validation using e1071:SVM
Hi everyone,
Can you help me to plot Gamma(x/h+1) and Beta(x/h+1,(1-x)/h+1)?I want write
x-seq(0,3,0.1)
thank
2010/11/23 Neeti nikkiha...@gmail.com
Hi everyone
I am trying to do cross validation (10 fold CV) by using e1071:svm method.
I
know that there is an option (cross) for cross validation but still I
wanted to make a function to Generate cross-validation indices using pls:
cvsegments method.
#
Code (at the end) Is working fine but sometime caret:confusionMatrix gives
following error:
stat_result- confusionMatrix(pred_true1,species_test)
Error in confusionMatrix.default(pred_true1, species_test) :
The data and reference factors must have the same number of levels
My data: total number=260
Class = 6
#
Sorry if I missed some previous discussion about this problem.
It would be nice if anyone explain or point out the mistake I am doing in
this following code.
Is there another way to do this? As I wanted to check my result based on
Accuracy and Kappa value generated by caret:confusionMatrix.
##
Code
#
x-NULL
index-cvsegments(nrow(data),10)
for(i in 1:length(index))
{
x-matrix(index[i])
testset-data[x[[1]],]
trainset-data[-x[[1]],]
species-as.factor(trainset[,ncol(trainset)])
train1-trainset[,-ncol(trainset)]
train1-train1[,-(1)]
test_t-testset[,-ncol(testset)]
species_test-as.factor(testset[,ncol(testset)])
test_t-test_t[,-(1)]
model_true1 - svm(train1,species)
pred_true1-predict(model_true1,test_t)
stat_result- confusionMatrix(pred_true1,species_test)
stat_true[[i]]-as.matrix(stat_result,what=overall)
kappa_true[i]-stat_true[[i]][2,1]
accuracy_true[i]-stat_true[[i]][1,1]
}
--
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http://r.789695.n4.nabble.com/cross-validation-using-e1071-SVM-tp3055335p3055335.html
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--
Francial Giscard LIBENGUE
Doctorant en Mathématiques Appliquées ;Option : Statistique
Université de Franche-Comté - UFR Sciences et Techniques
Laboratoire de Mathématiques de Besançon UMR 6623 CNRS
16, route de Gray - 25030 Besançon cedex, France.
Tel. +333.81.66.63.98 ; Fax +33 381 666 623 ; Bureau B 328.
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] cross validation using e1071:SVM
@Francial Giscard LIBENGUE please post your query again so that with different subject -- View this message in context: http://r.789695.n4.nabble.com/cross-validation-using-e1071-SVM-tp3055335p3055831.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] cross validation using e1071:SVM
could anyone help me with my last problem. if the question is not clear
please let me know
thank you
Hi everyone
I am trying to do cross validation (10 fold CV) by using e1071:svm method.
I
know that there is an option (cross) for cross validation but still I
wanted to make a function to Generate cross-validation indices using pls:
cvsegments method.
#
Code (at the end) Is working fine but sometime caret:confusionMatrix gives
following error:
stat_result- confusionMatrix(pred_true1,species_test)
Error in confusionMatrix.default(pred_true1, species_test) :
The data and reference factors must have the same number of levels
My data: total number=260
Class = 6
#
Sorry if I missed some previous discussion about this problem.
It would be nice if anyone explain or point out the mistake I am doing in
this following code.
Is there another way to do this? As I wanted to check my result based on
Accuracy and Kappa value generated by caret:confusionMatrix.
##
Code
#
x-NULL
index-cvsegments(nrow(data),10)
for(i in 1:length(index))
{
x-matrix(index[i])
testset-data[x[[1]],]
trainset-data[-x[[1]],]
species-as.factor(trainset[,ncol(trainset)])
train1-trainset[,-ncol(trainset)]
train1-train1[,-(1)]
test_t-testset[,-ncol(testset)]
species_test-as.factor(testset[,ncol(testset)])
test_t-test_t[,-(1)]
model_true1 - svm(train1,species)
pred_true1-predict(model_true1,test_t)
stat_result- confusionMatrix(pred_true1,species_test)
stat_true[[i]]-as.matrix(stat_result,what=overall)
kappa_true[i]-stat_true[[i]][2,1]
accuracy_true[i]-stat_true[[i]][1,1]
}
--
View this message in context:
http://r.789695.n4.nabble.com/cross-validation-using-e1071-SVM-tp3055335p3055836.html
Sent from the R help mailing list archive at Nabble.com.
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] cross validation using e1071:SVM
Neeti, I'm pretty sure that the error is related to the confusionMAtrix call, which is in the caret package, not e1071. The error message is pretty clear: you need to pas in two factor objects that have the same levels. You can check by running the commands: str(pred_true1) str(species_test) Also, caret can do the resampling for you instead of you writing the loop yourself. Max __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
