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Heart disease classification ensemble optimization using Genetic algorithm

机译:基于遗传算法的心脏病分类集成优化

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摘要

Heart disease diagnosis is considered as one of the complicated tasks in medical field. In order to perform heart disease diagnosis an accurate and efficient automation system can be very helpful. In this research, we propose a classifier ensemble method to improve the decision of the classifiers for heart disease diagnosis. Homogeneous ensemble is applied for heart disease classification and finally results are optimized by using Genetic algorithm. Data is evaluated by using 10-fold cross validation and performance of the system is evaluated by classifiers accuracy, sensitivity and specificity to check the feasibility of our system. Comparison of our methodology with existing ensemble technique has shown considerable improvements in terms of classification accuracy.
机译:心脏病诊断被认为是医学领域中的一项复杂任务。为了执行心脏病诊断,准确而有效的自动化系统可能会非常有帮助。在这项研究中,我们提出了一种分类器集成方法,以改善用于心脏病诊断的分类器的决策。将均质集合用于心脏病分类,最后使用遗传算法对结果进行优化。通过使用10倍交叉验证对数据进行评估,并通过分类器的准确性,敏感性和特异性评估系统的性能,以检查我们系统的可行性。我们的方法与现有集成技术的比较显示出分类准确性方面的显着提高。

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