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Journal of Ambient Intelligence and Humanized Computing, 2019
Association rules mining (ARM) is one of the most popular tasks of data mining. Although there are many effective algorithms run on binary or discrete-valued data for the problem of ARM, these algorithms cannot run efficiently on data that have numeric-valued attributes.
Elif Varol Altay, Bilal Alatas
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Association rules mining (ARM) is one of the most popular tasks of data mining. Although there are many effective algorithms run on binary or discrete-valued data for the problem of ARM, these algorithms cannot run efficiently on data that have numeric-valued attributes.
Elif Varol Altay, Bilal Alatas
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2014 9th International Conference on Industrial and Information Systems (ICIIS), 2014
It has been observed that sometimes in Numeric Association Rule Mining (NARM), it is important to understand the association between a numeric attribute and a specific categorical consequent class attribute. NARM divides the domain of numeric attributes sub-domains without considering particular categorical consequent class attribute.
Pradeep Kumar Saini +2 more
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It has been observed that sometimes in Numeric Association Rule Mining (NARM), it is important to understand the association between a numeric attribute and a specific categorical consequent class attribute. NARM divides the domain of numeric attributes sub-domains without considering particular categorical consequent class attribute.
Pradeep Kumar Saini +2 more
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2017
In recent years, many new applications, such as location-based services, sensor monitoring systems, and data integration, have shown a growing amount of importance of uncertain data mining. In addition, due to instrument errors, imprecise of sensor monitoring systems, and so on, real-world data tend to be numerical data with inherent uncertainty. Thus,
Bin Pei, Fenmei Wang, Xiuzhen Wang
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In recent years, many new applications, such as location-based services, sensor monitoring systems, and data integration, have shown a growing amount of importance of uncertain data mining. In addition, due to instrument errors, imprecise of sensor monitoring systems, and so on, real-world data tend to be numerical data with inherent uncertainty. Thus,
Bin Pei, Fenmei Wang, Xiuzhen Wang
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Association Rules Mining based on Numeric Constraint
INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences, 2012Yan Hai -, Zhang Tietou -
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A survey on association rule mining based on evolutionary algorithms
International Journal of Computers and Applications, 2021Bodrunnessa Badhon +2 more
exaly
The Combination of Evolutionary Algorithm Method for Numerical Association Rule Mining Optimization
Advances in Intelligent Systems and Computing, 2017Tahyudin +2 more
exaly