自爱
发表于 2025-3-23 11:19:07
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canonical
发表于 2025-3-23 14:51:53
Stella M. Valenzuelaand DBROUGH/ GRG, are described. DBLEARN is a system for discovering knowledge in databases (data mining) by performing attribute-oriented induction integrating learning-from-examples with set-oriented database operations. DBLEARN extracts generalized data from databases by applying concept tree asc
喊叫
发表于 2025-3-23 18:15:28
Adam I. Mechlerd of one knowledge base for the classification of new object, hoping that the combination of answers of multiple knowledge bases result in better performance. Multiple knowledge bases can be formulated precisely and in an unified way within the framework of rough sets theory. Our approach is based o
RUPT
发表于 2025-3-24 01:35:10
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议程
发表于 2025-3-24 05:19:35
tems, statistics, and expert systems. Data mining has evolved into an important and active area of research because of theoretical challenges and practical applications associated with the problem of discovering (or extracting) interesting and previously unknown knowledge from very large real-world
gain631
发表于 2025-3-24 09:49:20
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spinal-stenosis
发表于 2025-3-24 12:03:13
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textile
发表于 2025-3-24 15:38:07
Stella M. Valenzuelaold increase in speed). DBROUGH is a rough set based knowledge discovery system which integrates database operations, rough set theory and machine learning methods (data generalization and data reduction). In the data reduction phase, rough sets techniques are applied to the generalized relation to
Generator
发表于 2025-3-24 20:55:33
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Heretical
发表于 2025-3-24 23:25:27
Till Böcking,J. Justin Gooding into a fuzzy model that usually consists of rules of fuzzy sets (membership functions). In formal logic, such a transformation is called an interpretation of the theory. Of course, interpretations are usually not unique. The collection of all such interpretations is a highly structured set of membe