Hi,
I'm been trying to get libsvm working with emscripten. Others on the group
have had success with this. Here's what I've done and the output:
---------------
$ emcc -O2 svm.cpp -o svm.bc && emcc -O2 svm-train.cpp -o svm-train.bc &&
emcc -O2 svm.bc svm-train.bc -o svm-test.js && node svm-test.js && node
svm-test.js heart_scale
Usage: svm-train [options] training_set_file [model_file]
options:
-s svm_type : set type of SVM (default 0)
0 -- C-SVC (multi-class classification)
1 -- nu-SVC (multi-class classification)
2 -- one-class SVM
3 -- epsilon-SVR (regression)
4 -- nu-SVR (regression)
-t kernel_type : set type of kernel function (default 2)
0 -- linear: u'*v
1 -- polynomial: (gamma*u'*v + coef0)^degree
2 -- radial basis function: exp(-gamma*|u-v|^2)
3 -- sigmoid: tanh(gamma*u'*v + coef0)
4 -- precomputed kernel (kernel values in training_set_file)
-d degree : set degree in kernel function (default 3)
-g gamma : set gamma in kernel function (default 1/num_features)
-r coef0 : set coef0 in kernel function (default 0)
-c cost : set the parameter C of C-SVC, epsilon-SVR, and nu-SVR (default 1)
-n nu : set the parameter nu of nu-SVC, one-class SVM, and nu-SVR (default
0.5)
-p epsilon : set the epsilon in loss function of epsilon-SVR (default 0.1)
-m cachesize : set cache memory size in MB (default 100)
-e epsilon : set tolerance of termination criterion (default 0.001)
-h shrinking : whether to use the shrinking heuristics, 0 or 1 (default 1)
-b probability_estimates : whether to train a SVC or SVR model for
probability estimates, 0 or 1 (default 0)
-wi weight : set the parameter C of class i to weight*C, for C-SVC (default
1)
-v n: n-fold cross validation mode
-q : quiet mode (no outputs)
can't open input file heart_scale
The error is: No such file or directory
=======================================
The file heart_scale is definitely in that directory. The libsvm code is
here: http://www.csie.ntu.edu.tw/~cjlin/libsvm/. (Note: I modified the
svm-train.cpp file a little in read_problem to give perror.)
Thanks,
-Dave
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