Results 121 to 130 of about 9,792 (165)

Fuzzy signatures in data mining

Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569), 2002
Fuzzy signature has a special role in data mining, concerning data mixed with human estimates. The semantics of the fuzzy concept is a relevant issue of data interpretation. A software system was developed to implement these ideas and works on a rather extensive database of a two-decade neuro-developmental project.
T. Vamos, L.T. Koczy, G. Biro
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Fuzzy MapReduce Data Mining algorithms

2018 International Conference on Fuzzy Theory and Its Applications (iFUZZY), 2018
The mining time complexity is more with the conventional MapReduce algorithm particularly with large data sets or big data. The existing MapReduce algorithms will take time and data sets have to be disclosed for analysis. Defining data inherently with fuzziness will reduce the retrieval time and actual data sets need not be disclosed.
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On a fuzzy querying and data mining interface

Kybernetika, 2000
Summary: An interface is proposed that combines flexible (fuzzy) querying and data mining functionality. The point of departure is the fuzzy querying interface designed and implemented previously by the present authors. It makes it possible to formulate and execute, against a traditional (crisp) database, queries containing imprecisely specified ...
Janusz Kacprzyk, Slawomir Zadrozny
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Data mining with ensembles of fuzzy decision trees

2009 IEEE Symposium on Computational Intelligence and Data Mining, 2009
In this paper, a study is presented to explore ensembles of fuzzy decision trees. First of all, a quick recall of the state of the art related to ensembles of (fuzzy) decision trees in Machine Learning is presented. Afterwards, a new approach to construct a forest of fuzzy decision trees is proposed.
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Fuzzy Models for Big Data Mining

2019
We are currently experiencing the Big Data Era [20]: large volume of information is generated by different sources and may have different formats (variety) [5].
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Data mining by attribute generalization with fuzzy hierarchies in fuzzy databases

Fuzzy Sets and Systems, 2009
In this paper we examine the soft computing issues involving data generalization on fuzzy information. The attribute induction process is formalized for these three cases: crisp hierarchy/fuzzy data; fuzzy hierarchy/crisp data; fuzzy hierarchy/fuzzy data. Each case is exemplified by applications of the algorithm to a prototype database.
Frederick E. Petry, Lei Zhao
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Fuzzy data mining based on the compressed fuzzy FP-trees

2009 IEEE International Conference on Fuzzy Systems, 2009
In this paper, we design the compressed fuzzy FP-tree structure to mine fuzzy frequent itemsets from the transactions with quantitative values. It consists of two phases. In the first phase, a compressed fuzzy frequent pattern tree (CFFP tree) is constructed from the given quantitative transactions.
Chun-Wei Lin 0001, Tzung-Pei Hong, Wen-Hsiang Lu   +2 more
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Fuzzy logic and data mining

Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium, 2002
There are many activities of both technology and its application in data mining and knowledge discovery in database area. In this paper, actual applications of data mining are presented from its development point of view, and a generalized conceptual model of data mining is proposed.
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Data mining and fuzzy modeling

Proceedings of North American Fuzzy Information Processing, 2002
Fuzzy models are constructs relying heavily on a qualitative domain knowledge and diverse optimization techniques. What makes them different from other models is their inherent embedding in the context of nonnumeric set or fuzzy set-oriented information.
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A fuzzy data mining algorithm for quantitative values

1999 Third International Conference on Knowledge-Based Intelligent Information Engineering Systems. Proceedings (Cat. No.99TH8410), 2003
This paper attempts to propose a new data-mining algorithm to enhance the capability of exploring interesting knowledge from transactions with quantitative values. The proposed algorithm integrates the fuzzy set concepts and the a priori mining algorithm to find interesting fuzzy association rules from given transaction data.
Tzung-Pei Hong, Chan-Sheng Kuo, Sheng-Chai Chi   +2 more
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