One-Class classification I am currently using an one class classification svm and I am trying to boost the classification results by employing more than one svm-occ with varying gamma parameters and combine these decisions with majority voting. But the results are not that satisfactory , since with a careful choice of gamma parameter I can get better results with just one-class svm. So , I was just wondering if I can employ also another one-class classifier e.g. SVDD and then combine its decisons with svm-occ . But the problem is my project is being developed in python enviroment and I can't find an implementation of SVDD with sklearn. So is there any suggestions which classifiers to use and if an according python implementation exists or how to combine them to obtain in overall better classification results ? (**I am keeping the nu parameter on svm-occ fixed)
Ummm... SVM is a linear model, so if you average the predictions of several models with different regularization, what you get is the same result of another model which uses a different regularization.
Regarding the intent behind your question: there's more methods than SVM and SVDD. You can check the PyOD package for ensemble models for outlier detection.