Extracting information from fuzzy models

被引：0
|
作者：
Silipo, Rosaria [1 ]
机构：
[1] Int Computer Science Inst, Berkeley, United States
来源：
Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS | 2000年
关键词：
Algorithms - Electrocardiography - Statistical methods;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The goal of this study is to quantify the importance of the input features in a fuzzy solution of two real-world problems. The first analysis defines the most effective ElectroCardioGraphic (ECG) measures for an automatic fuzzy recognition of cardiac arrhythmic beats. The second problem aims to assess the role played by duration, amplitude and pitch features of vocalic nuclei for the automatic recognition of prosodic stress in spoken American English. A similar analysis is performed for both problems by means of statistical decision trees under the form of the C4.5 algorithm. In general, decision trees and fuzzy systems seem to exploit the same or related input features for the analysis, especially if the input space dimension is low.
引用
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页码：44 / 48
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