Displaying 5 results from an estimated 5 matches for "svmtrain".
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2009 Sep 17
2
SVM
Hello,
I have 12 sample each sample has got 1000 observation, i.e I have a matrix X with 1000 rows and 12 columns!
m <- svm(t(X))
p <- predict (m)
Can anyone tell me how to use svmtrain() in R!
Many Yhanks,
Samuel
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2009 Oct 14
0
Confusion matrix from cross validation in R:
Hey!
How do I get the confusion matrix after performing 10-fold cross validation
from SVM in R?
When I try to print it, I get the confusion matrix without cross validation.
I need to compute PPV. Should I report PPV without CV and total accuracy
with CV?
I am confused.
> svmtrain <- svm(xtrain,ytrain,kernel="sigmoid",cross=10)
> pred <- predict(svmtrain, xtrain)
> table(pred, ytrain)
Pam
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2011 Jan 21
1
help! complete the reviewer's suggest: carry out GA+GP (gaussian process)!
...vm: libsvm (http://www.csie.ntu.edu.tw/~cjlin/libsvm/)
now I want to know, how to get the predicted values :
In libsvm for example:
cmd = ['-v ',num2str(v),' -c',num2str(cgp(nind,1)), '-g
',num2str(cgp(nind,2)),' -p ',num2str(cgp(nind,3)),' -s 3'];
model = svmtrain(train_y,train_data_best,cmd);
train_pred = svmpredict(train_y,train_data_best,model); % get the predicted
values for the training set
I can get the train_pred, likewise I can get the test_pred (tes_pred =
svmpredict(test_y,test_data_best,model);)
If I have the obsved train_y,test_y and the predic...
2002 Jun 21
3
Question
Hallo,
once again I have a question. Maybe someone can help me.
I call in my programm (VC++) the Rterm.exe via "Rterm.exe --no-restore
--no-save < example.R >example.Rout".
In example.R :
temperaturfeld <- read.table(file.choose(), header = TRUE, sep= "",
comment.char = "#")
temperaturmatrix <- data.matrix(temperaturfeld)
windows()
2011 Jan 22
0
how to call BayesX in R to see the graph
.../<http://www.csie.ntu.edu.tw/%7Ecjlin/libsvm/>
)
now I want to know, how to get the predicted values :
In libsvm for example:
cmd = ['-v ',num2str(v),' -c',num2str(cgp(nind,1)), '-g
',num2str(cgp(nind,2)),' -p ',num2str(cgp(nind,3)),' -s 3'];
model = svmtrain(train_y,train_data_best,cmd);
train_pred = svmpredict(train_y,train_data_best,model); % get the predicted
values for the training set
I can get the train_pred, likewise I can get the test_pred (tes_pred =
svmpredict(test_y,test_data_best,model);)
If I have the obsved train_y,test_y and the predic...