I'm looking for some papers to read to get started understanding classifier selection method in a computer security system.

I wanted to develop a Multiple Classifier System based on a pool of classifier (heterogenous classifiers). The idea is like the system will select the most competent algorithm for a particular dataset using the classifier selection method.

Could you suggest me some papers in computer security (like intrusion detection for example) or other areas that employ the method?


A lot of the activity currently going on around 'automated machine learning' / 'AutoML' goes into that direction, although it is not limited to the selection of a classification model.

While I won't provide a literature review on the topic here, I think having a look at what papers cite AutoML and similar projects might give you the results you are looking for.


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