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ThunderSVM: A Fast SVM Library on GPUs and CPUs

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I have tried to install the thundersvm-gpu with CUDA 10.1 in ubuntu 18.04 But, the official thunder svm package cannot be supported with over cuda 10.0 When i call the...

I need to process a big training data with `OneVsRestClassifier(SVC)` model. Due to training data size, i need GPU support, so i moved from `sklearn` to `thundersvm`. But after replacing,...

enhancement

Here I have listed all the steps to install and use thundersvm. Some comparison speedups of thundersvm with scikit-learn svm is also shown here. Follow these to get started with...

call for contribution

Hi, I'm trying to train a C-SVM or OneClassSVM using the Python API or CLI tools, both failed to allocate cuda memory on master branch. Although I limit the memory...

Hello, Is there any way to improve the documentation or clarifiy here how it is possible to obtain classification scores from ONE class SVM as in scikit-learn score_samples function. I...

call for contribution

Hello. I want to get the coefficients of linear svm for my own desicion funciton(y=w*x+b), and try in this way: ``` w = model.coef_.T b = model.intercept_ ``` but the...

I am able to run thundersvm but under certain multithreaded environments I get this error: `lib/python3.6/site-packages/thundersvm-0.3.4-py3.6.egg/thundersvm/thundersvm.py", line 237, in _dense_fit n_classes, self._train_succeed, c_void_p(self.model)) ctypes.ArgumentError: argument 19: : Don't know how...

Hey! I'm running the library on Google Colaboratory. I am running to issues where fitting of a classifier hangs. Sometimes the same data-set runs in few minutes, and rest of...

Often when running eps-SVR with cross-validation, the final fold fails with a similar error: ``` INFO [default] working set size = 0 FATAL [default] Check failed: [((data)) != nullptr] WARNING...

call for contribution

Dear developers, first of all, thank you for the GPU implementation of SVM, it works really good (especially for the prediction task). I have the following problem: I use ThunderSVM...

enhancement