An improved CBA prediction algorithm in compound pyramid model

As one of KDTICM 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, multilayer 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.