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ThunderSVM: A Fast SVM Library on GPUs and CPUs

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Hi, I am tuning hyperparameters using Scikit's GridSearchCV as such: `grid = GridSearchCV(SVC(), param_grid, refit = True, verbose=3, cv=skf.split(x,y), n_jobs=-1, scoring = 'accuracy')` and I get this error... `BrokenProcessPool: A...

Hi, For the past days I've been trying to use this library together with sklearn's GridSearchCV in order to find the best parameters for an SVR regressor over some data...

Hello, I try to use thundersvm for train the svm on my local gpu with jupyter notebook. I installed thundersvm as described here (https://github.com/Xtra-Computing/thundersvm/blob/master/docs/get-started.md) and it worked after I Had...

Hi, I have a problem to use thundersvm. After installing CUDA 9.0 version and installed thundersvm by` pip install thundersvm`. But still I have an error that > ModuleNotFoundError: No...

Hi, I am getting this error: 2021-05-03 15:29:31,316 FATAL [default] Check failed: [error == cudaSuccess] unknown error 2021-05-03 15:29:31,316 WARNING [default] Aborting application. Reason: Fatal log at [/home/hanfeng/tmp/tsvm/src/thundersvm/thundersvm-scikit.cpp:154] any ideas...

I made a code that does multi class svm and it is utilizing the gpu correctly on linux however on windows it isnt using the gpu i have installed the...

I am using the latest master branch of thundersvm. Compared to serial sklearn (LibSVM), thundersvm is orders of magnitude slower. I am probably doing something wrong though. I have tested...

enhancement

Hello, I have a question about the functions of predict and predict_proba. When I run the codes like: fine_labels = clf.predict(fine_cells) fine_probs = clf.predict_proba(fine_cells) print(fine_labels ) print(fine_probs) the outcomes is:...

Hi, the efficiency of thundersvm is very appealing, and I want to try the thundersvm software on Matlab. However, I can't get the software installed though following the document. Can...

call for contribution

_sklearn.metrics.precision_recall_curve(y_true, probas_pred, *, pos_label=None, sample_weight=None)_ According to Sklearn, we should pass a probability prediction as a parameter for precision_recall_curve. But, the OCSVM doesn't have a function that returns a probability...

enhancement
call for contribution