Feature Weight and Its Application in Weight Determination of Medical Scale Items

Zhenhua Wang, Zhongsheng Hou, Ying Gao, Qiang Liu
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Abstract

Actually, the determination of medical scales items is feature weight problem in data-mining area. The framework of EC-based (Evolutionary computation) classification method for feature weight is presented contrasted with traditional statistical methods. And an improved EC-based k-NN algorithm for feature weight, GS-k-NN, is put forward and presented. Comparison between PSO and GA is made as well as among k-NN, GS-k-NN, C4.5, SVM in the paper. Results show that PSO-based GS-k-NN is more effective than other algorithms.
特征权重及其在医用秤项目重量测定中的应用
医学尺度项目的确定实际上是数据挖掘领域的特征权重问题。提出了基于进化计算的特征权重分类方法框架,并与传统的统计方法进行了对比。并提出了一种改进的基于ec的k-NN特征权值算法GS-k-NN。本文对粒子群算法与遗传算法进行了比较,并对k-NN、GS-k-NN、C4.5、SVM进行了比较。结果表明,基于pso的GS-k-NN比其他算法更有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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