Implementing One Class SVM in PyTorch

1

Is it possible to implement One Class SVM as a part of a Neural Network in PyTorch?

I am doing an experiment for my research on outlier detection and I need to implement One Class SVM as a layer and its objective function as apart of the main objective / loss function. I know I could use ScikitLearn and LibSVM for the same. But my experiment needs it to be a part of a neural network ensemble I am building. So the weights should be iteratively learnable with the other parameters of the NN.

Any help or pointers would be appreciated.

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You could try to use e.g. nn.MultiLabelMarginLoss, which is the multi-classification hinge loss and create the desired targets for your “One Class SVM”.

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