optimal classification algorithm

I would like to know, from the below classification algorithm which one is optimal(in terms of memory and processing power) and which classific开发者_如何学Pythonation algorithm used widely?

• k-Nearest Neighbor(KNN) Algorithm
• Naive Bayesian(NB) Algorithm
• Concept Vector-based(CB) Algorithm
• Singular Value Decomposition-based Algorithm
• Hierarchical Algorithm
• Combination Algorithm
• SVM

I am looking for an optimal algorithm to classify network traffic.

Thank you!

-sathish

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The statement that there is no single best classification method is one of the No Free Lunch theorems - http://www.no-free-lunch.org/ Since you mention processing time and memory requirements I note that Naive Bayes is pretty cheap and has been good enough to be used in practice.

At http://www.cs.waikato.ac.nz/ml/weka/ you can pick up a lot of ready-implemented methods and a framework that will allow you to try them out and compare them.

Very often what features you pick out to feed into your classification method is more important than what method you chose.

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IMO, SVM is best one and currently used in many application.