A Strategic Study of Mining Fuzzy Association Rules Using Fuzzy Multiple Correlation Measues
نویسندگان
چکیده
منابع مشابه
Fuzzy Correlation Rules Mining
General fuzzy association rules mining focuses on finding out the fuzzy itemsets or fuzzy attributes which frequently occur together. But two fuzzy itemsets which frequently occur together can not imply that there is always an interesting relationship between them. In this paper, we develop an alternative framework for mining interesting relationship between fuzzy itemsets based on fuzzy correl...
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Mining fuzzy association rules is the task of finding the fuzzy itemsets which frequently occur together in large fuzzy dataset, but most proposed methods may identify a fuzzy rule with two fuzzy itemsets as interesting when, in fact, the presence of one fuzzy itemsets in a record does not imply the presence of the other one in the same record. To prevent generating this kind of misleading fuzz...
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Data mining is the process of extracting desirable knowledge or interesting patterns from existing databases for specific purposes. Many types of knowledge and technology have been proposed for data mining. Among them, finding association rules from transaction data is most commonly seen. Most studies have shown how binary valued transaction data may be handled. Transaction data in real-world a...
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Association rules (ARs) (Agrawal, Imielinski & Swami, 1993) are a well established data mining technique used to discover co-occurrences of items mainly in market basket data. An item is usually a product amongst a list of other products and an itemset is a combination of two or more products. The items in the database are usually recorded as binary data (present or not present). The technique ...
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ژورنال
عنوان ژورنال: Journal of Algorithms & Computational Technology
سال: 2012
ISSN: 1748-3026,1748-3026
DOI: 10.1260/1748-3018.6.3.499