An Application of PSO Algorithm and Decision Tree for Medical Problem
نویسنده
چکیده
In this study, we propose a novel method for medical problem, it is the integration of particle swarm optimization (PSO) and decision tree (C4.5) named PSO + C4.5 algorithm. To evaluate the effectiveness of PSO + C4.5 algorithm, it is implemented on 5 different data sets of life sciences obtained from UCI machine learning databases. Moreover, the results of PSO + C4.5 implementation are compared to logistic regression (LR), back propagation neural network (BPNN), support vector machine (SVM), and decision tree (C4.5). The accuracy index shows that PSO + C4.5 algorithm outperforms the other methods. Keywords—Decision tree, Feature selection, Particle swarm optimization.
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