An improved CBA prediction algorithm in compound pyramid model

Authors:
Zhou Zhun;Yang Bingru;Hou Wei
Affiliations:
University of Science and Technology Beijing, Information Engineering School, Beijing;University of Science and Technology Beijing, Information Engineering School, Beijing;University of Science and Technology Beijing, Information Engineering School, Beijing
Venue:
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Year:
2009

Citing 4
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Abstract

As one of KDTICM[8] theory researches, this paper propose an improved algorithm -- CBA, which is based on KDD* model and combined with KAAPRO method, for protein secondary structure prediction problem. Further, multi-layer systematic prediction model--Compound Pyramid Model, is proposed. The kernel of this model is CBA which is a classic association rules analysis algorithm. Domain knowledge is used through the model, and the phy-chemical attributes is chosen by Causal Cellular Automation. In experiment, the proteins bias alpha/beta structure are precisely predicted. The structures of amino acids, whose structure are obscure, are predicted well by the improved CBA. Finally, the result of this model is satisfied.