Protein Secondary Structure Prediction with Support Vector Machines
نویسنده
چکیده
In this paper, a method for secondary structure with support vector machines is presented. The system used two layers of support vector machines, with a weighted cost function to balance the uneven class memberships. Using this method, prediction accuracy reaches 71.5%, comparable to the best techniques avaliable.
منابع مشابه
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