Displaying 7 results from an estimated 7 matches for "vanilladot".
2008 Jun 25
1
stringdot
...ne,kernel="rbfdot",C=10,cross=5)# works fine with the rbf kernel
gene.string <- ksvm(Class~.,data=promotergene,kernel="stringdot",C=10,cross=5) # this give the following error
#Error in match.arg(kernel, c("rbfdot", "polydot", "tanhdot", "vanilladot", :
# 'arg' should be one of ?rbfdot?, ?polydot?, ?tanhdot?, ?vanilladot?, ?laplacedot?, ?besseldot?, ?anovadot?, ?splinedot?, ?matrix?
What am I doing wrong here?
Thanks ../Murli
2011 Oct 06
0
linear classifiers with sparse matrices
...LiblineaR(SM1,L1)
Error in t.default(data) : argument is not a matrix
Setting default kernel parameters
> predict(model,DM)
[,1]
[1,] 0.1
[2,] 0.9
[3,] 0.1
[4,] 0.9
[5,] 0.1
[6,] 0.9
[7,] 0.1
[8,] 0.9
[9,] 0.1
[10,] 0.9
> model = ksvm(SM1,L1,scale=FALSE,kernel="vanilladot")
Error in function (classes, fdef, mtable) :
unable to find an inherited method for function "ksvm", for
signature "dgCMatrix"
> model = ksvm(SM2,L1,scale=FALSE,kernel="vanilladot")
Error in function (classes, fdef, mtable) :
unable to find an inherited...
2008 Sep 14
0
ksvm accessing the slots of S4 object
I am using kernlab to build svm models. I am not sure how to access the different slots of the object. For instance if I want to get the nuber of support vectors for each of model I am building and store it in a vector.
>ksvm.model <- ksvm(Class ~ ., data = somedata,kernel = "vanilladot", cross = 10, type ="C-svc")
>names(attributes(ksvm.model))
[1] "param" "scaling" "coef" "alphaindex" "b"
[6] "obj" "SVindex" "nSV" "prior" "prob.mod...
2011 May 26
0
R svm prediction kernlab
...se the updated svm weights in the
predict method framework. I don't know if its possible or not, how do
classify new data using predict method? Is it possible to build a new ksvm
object using new weights?
Weight calculation is as follows:
svp <- ksvm(x,y,type="C-svc", kernel="vanilladot",C=1)
w <- colSums(coef(svp)[[j]] * x[unlist(alphaindex(svp)[[j]]),])
b <- b(svp)[[j]]
for all j = 1:N(N-1)/2 where N is number of classes
Alternately, I implemented the majority voting myself to perform the
classification , but I am getting slightly different results from
predict.svm...
2011 Dec 08
0
SVM performance using laplace kernel is too slow
...ions using data mining algorithms in SQL Server analysis services run about 40x faster.
Through trial and error, we discovered that the laplacedot kernel gives us the best results by a wide margin. Rbfdot is about 15% less accurate, but twice as fast (but still too slow). The best performance is vanilladot. It runs more or less instantly but the accuracy is way too low to use.
We'd ideally like to use the laplacedot kernel but to do so we need a massive speedup. Does anyone have any ideas on how to do this?
Here is some profiling information I generated using rprof. It looks like most of th...
2012 Feb 13
2
kernlab - error message: array(0, c(n, p)) : 'dim' specifies too large an array
Hi,
For another trainingset I get this error message, which again is rather cryptic to me:
Setting default kernel parameters
Error in array(0, c(n, p)) : 'dim' specifies too large an array
RMate stopped at line 0 of selection
Calls: rvm ... .local -> backsolve -> as.matrix -> chol -> diag -> array
thanks for any suggestions!
2010 Sep 24
0
kernlab:ksvm:eps-svr: bug?
...shrinking = TRUE,
64 ...
65 ,subset
66 ,na.action = na.omit)
67 {
...
74 sparse <- FALSE
75
76 if(is.character(kernel)){
77 kernel <- match.arg(kernel,c("rbfdot","polydot","tanhdot","vanilladot","laplacedot","besseldot","anovadot","splinedot","matrix"))
78
79 if(kernel == "matrix")
80 if(dim(x)[1]==dim(x)[2])
81 return(ksvm(as.kernelMatrix(x), y = y, type = type, C = C, nu = nu, epsilon =...