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    Protein Secondary Structure Prediction with Dynamic Self-Adaptation Combination Strategy Based on Entropy

    Yuehan Du1,2, Ruoyu Zhang1, Xu Zhang1, Antai Ouyang3, Xiaodong Zhang4, Jinyong Cheng1, Wenpeng Lu1,*

    Journal of Quantum Computing, Vol.1, No.1, pp. 21-28, 2019, DOI:10.32604/jqc.2019.06063

    Abstract The algorithm based on combination learning usually is superior to a single classification algorithm on the task of protein secondary structure prediction. However, the assignment of the weight of the base classifier usually lacks decision-making evidence. In this paper, we propose a protein secondary structure prediction method with dynamic self-adaptation combination strategy based on entropy, where the weights are assigned according to the entropy of posterior probabilities outputted by base classifiers. The higher entropy value means a lower weight for the base classifier. The final structure prediction is decided by the weighted combination of posterior probabilities. Extensive experiments on CB513… More >

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