Comparative Analysis Of Dempster Shafer Method With Certainty Factor Method For Diagnose Stroke Diseases
نویسندگان
چکیده
منابع مشابه
Data classification using the Dempster-Shafer method
In this paper, the Dempster-Shafer method is employed as the theoretical basis for creating data classification systems. Testing is carried out using three popular (multiple attribute) benchmark datasets that have two, three and four classes. In each case, a subset of the available data is used for training to establish thresholds, limits or likelihoods of class membership for each attribute, a...
متن کاملAnomaly Detection Using the Dempster-Shafer Method
In this paper, we implement an anomaly detection system using the Dempster-Shafer method. Using two standard benchmark problems we show that by combining multiple signals it is possible to achieve better results than by using a single signal. We further show that by applying this approach to a real-world email dataset the algorithm works for email worm detection. Dempster-Shafer can be a promis...
متن کاملA Network Intrusion Detection Method Using Dempster-shafer Theory
An intrusion detection system (IDS) detects unauthorized manipulations of computer systems. Operation as feature reduction (including feature extraction and feature selection) plays an important role in the sense of improving classification performance and reducing the computational complexity of intrusion detection system. Feature reduction is even more important at online detection when less ...
متن کاملAlgorithms for Dempster-Shafer Theory
The method of reasoning with uncertain information known as Dempster-Shafer theory arose from the reinterpretation and development of work of Arthur Dempster [Dempster, 67; 68] by Glenn Shafer in his book a mathematical theory of evidence [Shafer, 76], and further publications e.g., [Shafer, 81; 90]. More recent variants of Dempster-Shafer theory include the Transferable Belief Model see e.g., ...
متن کاملDempster-Shafer for Anomaly Detection
two standard benchmark problems we show that by combining multiple signals it is possible to achieve better results than by using a single signal. We further show that by applying this approach to a real-world email dataset the algorithm works for email worm detection. Dempster-Shafer can be a promising method for anomaly detection problems with multiple features (data sources), and two or more...
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ژورنال
عنوان ژورنال: International Journal of Artificial Intelligence Research
سال: 2018
ISSN: 2579-7298
DOI: 10.29099/ijair.v2i1.53