Abstract
Data mining technology has important clinical significance for disease classification and prevention. In order to improve the performance of the model and the accuracy of disease classification, this paper proposes KPCA-IBA-LSSVM model. In view of the high dimensionality and nonlinearity of medical data, KPCA is used to reduce dimension. BA algorithm is used to optimize the parameters of LSSVM. At the same time, BA algorithm is easy to fall into local extreme and premature convergence. So this paper improves BA algorithm from three aspects. Finally, in order to verify the validity of the algorithm, this paper uses Breast Cancer, Statlog (Heart) and Heart Disease datasets from UCI machine learning database to validate the model. The simulation results show that the model has achieved better classification accuracy, and the model can also be used for classification and prediction of other diseases. The method proves to have certain feasibility and promotion.
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