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Intelligent optimization algorithms for the problem of mining numerical association rules
Physica A: Statistical Mechanics and its Applications, 2020Abstract There are many effective approaches that have been proposed for association rules mining (ARM) on binary or discrete-valued data. However, in many real-world applications, the data usually consist of numerical values and the standard algorithms cannot work or give promising results on these datasets.
Elif Varol Altay, Bilal Alatas
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Mining Association Rules on Related Numeric Attributes
1999In practical applications, some property is represented by a pair of related attributes. For example, blood pressure, temperature changes etc. The existing data mining approaches for association rules can not tackle those cases, because they treat every attribute independently.
Xiaoyong Du 0001 +2 more
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Wolf search algorithm for numeric association rule mining
2016 IEEE International Conference on Cloud Computing and Big Data Analysis (ICCCBDA), 2016Big data has become one of the key sources for valuable information and as information becomes larger it poses some computational challenge in finding a best possible solution for mining association rules and discovering patterns in data. Meta-heuristic algorithm when applied to mining association rules aims to find best possible rules from data ...
Israel Edem Agbehadji +2 more
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Mining numerical association rules via multi-objective genetic algorithms
Information Sciences, 2013Association rule discovery is an ever increasing area of interest in data mining. Finding rules for attributes with numerical values is still a challenging point in the process of association rule discovery. Most of popular methods for association rule mining cannot be applied to the numerical data without data discretization.
Behrouz Minaei-Bidgoli +2 more
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Sensitivity Analysis of MODENAR Method for Mining of Numeric Association Rules
2019 1st International Informatics and Software Engineering Conference (UBMYK), 2019There are many association rules mining studies that focus on datasets consisting of only discrete or binary valued attributes. However, the data in many real-world applications are generally composed of quantitative or numeric values and classical association rule mining methods do not automatically work without preprocessing that disrupt the real ...
Elif Varol Altay, Bilal Alatas
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MODENAR: Multi-objective differential evolution algorithm for mining numeric association rules
Applied Soft Computing, 2008In this paper, a Pareto-based multi-objective differential evolution (DE) algorithm is proposed as a search strategy for mining accurate and comprehensible numeric association rules (ARs) which are optimal in the wider sense that no other rules are superior to them when all objectives are simultaneously considered.
Bilal Alatas, Erhan Akin, Ali Karci
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Analyzing patterns of numerously occurring heart diseases using association rule mining
2017 Twelfth International Conference on Digital Information Management (ICDIM), 2017The use of technology and science in Healthcare has made services available to all the people along with ensuring the best care for the people. Data Mining provides us such useful techniques, which can help the medical practitioners to effectively analyze and discover large amount of data in a more efficient and convenient way as now electronic ...
K. M. Mehedi Hasan Sonet +4 more
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Grand Reports: A Tool for Generalizing Association Rule Mining to Numeric Target Values
2020Since its introduction in the 1990s, association rule mining(ARM) has been proven as one of the essential concepts in data mining; both in practice as well as in research. Discretization is the only means to deal with numeric target column in today’s association rule mining tools.
Sijo Arakkal Peious +4 more
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Improving Association Rule Mining Using Clustering-based Discretization of Numerical Data
2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC), 2018Association rule mining is an important data mining technique that help discover interesting attribute relationships that are useful for decision making. Most association rule mining methods use item-set manipulation approach, whereby data type must be categorical in nature. When a dataset contains numerical attributes, they will need to be discretized
Swee Chuan Tan
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Multi-objective PSO algorithm for mining numerical association rules without a priori discretization
Expert Systems with Applications, 2014In the domain of association rules mining (ARM) discovering the rules for numerical attributes is still a challenging issue. Most of the popular approaches for numerical ARM require a priori data discretization to handle the numerical attributes. Moreover, in the process of discovering relations among data, often more than one objective (quality ...
Vahid Beiranvand +2 more
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