Analysing Rough Sets weighting methods for Case-Based Reasoning Systems
نویسندگان
چکیده
منابع مشابه
Analysing Rough Sets weighting methods for Case-Based Reasoning Systems
Case-Based Reasoning systems retrieve cases using a similarity function based on the K-NN or some derivatives. These functions are sensitive to irrelevant, interacting or noisy features. Many similarity functions weigh the relevance of features to avoid this problem. This article proposes two weighting methods based on Rough Sets theory: Proportional Rough Sets and Dependence Rough Sets. Both w...
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Case-Based Reasoning systems usually retrieve cases using a similarity function based on K-NN or some derivatives. These functions are sensitive to irrelevant or noisy features. Weighting methods are used to extract the most important information present in the knowledge and determine the importance of each feature. However, this knowledge, can also be incorrect, redundant and inconsistent. In ...
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Problem of knowledge analysis for decision support system is the most difficult task of information systems. This paper presents a new approach based on notions of mathematical theory of Rough Sets to solve this problem. Using these concepts a systematic approach has been developed to reduce the size of decision database and extract reduced rules set from vague and uncertain data. The method ha...
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ژورنال
عنوان ژورنال: INTELIGENCIA ARTIFICIAL
سال: 2002
ISSN: 1988-3064,1137-3601
DOI: 10.4114/ia.v6i15.753