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Showing 1 to 2 of 2 for “"Attribute Implications"”.
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Relational Approach to the L-Fuzzy Concept Analysis
… and processing of objects and their attributes. In general, the object classification procedure can coincide with vagueness. Vagueness is a common problem in object analysis that exists at various stages of classification, including ambiguity in input data, overlapping boundaries …
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Data mining using L-fuzzy concept analysis.
Association rules in data mining are implications between attributes of objects that hold in all instances of the given data. These rules are very useful to determine the properties of the data such as essential features of products that determine the purchase decisions of customers. Normally the …