Comput Math Methods Med - Determination of fetal state from cardiotocogram using LS-SVM with particle swarm optimization and binary decision tree.

Tópicos

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{ detect(2391) sensit(1101) algorithm(908) }

Resumo

We use least squares support vector machine (LS-SVM) utilizing a binary decision tree for classification of cardiotocogram to determine the fetal state. The parameters of LS-SVM are optimized by particle swarm optimization. The robustness of the method is examined by running 10-fold cross-validation. The performance of the method is evaluated in terms of overall classification accuracy. Additionally, receiver operation characteristic analysis and cobweb representation are presented in order to analyze and visualize the performance of the method. Experimental results demonstrate that the proposed method achieves a remarkable classification accuracy rate of 91.62%.

Resumo Limpo

use least squar support vector machin lssvm util binari decis tree classif cardiotocogram determin fetal state paramet lssvm optim particl swarm optim robust method examin run fold crossvalid perform method evalu term overal classif accuraci addit receiv oper characterist analysi cobweb represent present order analyz visual perform method experiment result demonstr propos method achiev remark classif accuraci rate

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