Dai Wenbin, Zhang Yuntao, Gao Xingyu
Institute of Applied Chemistry, China West Normal University, Nanchong 637002, China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2009 Feb;26(1):38-41.
GEP (Gene expression programming) is a new genetic algorithm, and it has been proved to be excellent in function finding. In this paper, for the purpose of setting up a diagnostic model, GEP is used to deal with the data of heart disease. Eight variables, Sex, Chest pain, Blood pressure, Angina, Peak, Slope, Colored vessels and Thal, are picked out of thirteen variables to form a classified function. This function is used to predict a forecasting set of 100 samples, and the accuracy is 87%. Other algorithms such as SVM (Support vector machine) are applied to the same data and the forecasting results show that GEP is better than other algorithms.
基因表达式编程（GEP）是一种新的遗传算法，并且已被证明在函数发现方面表现出色。在本文中，为了建立一个诊断模型，GEP被用于处理心脏病数据。从13个变量中挑选出8个变量，即性别、胸痛、血压、心绞痛、峰值、斜率、血管颜色和地中海贫血，以形成一个分类函数。该函数用于预测一组100个样本的预测集，准确率为87%。其他算法，如支持向量机（SVM），也应用于相同的数据，预测结果表明GEP比其他算法更好。
