Results 221 to 230 of about 89,998 (265)

Learning Fuzzy Association Rules and Associative Classification Rules

2006 IEEE International Conference on Fuzzy Systems, 2006
Learning association rules and/or associative classification rules has been extensively studied in data mining and knowledge discovery community. Associative classification rules are considered as constrained association rules. Mining traditional association rules from transaction databases, however, has suffered some limitations.
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Optimising synaptic learning rules in linear associative memories

Biological Cybernetics, 1991
Associative matrix memories with real-valued synapses have been studied in many incarnations. We consider how the signal/noise ratio for associations depends on the form of the learning rule, and we show that a covariance rule is optimal. Two other rules, which have been suggested in the neurobiology literature, are asymptotically optimal in the limit ...
Dayan, P., Willshaw, D.
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Explainability with Association Rule Learning for Weather Forecast

SN Computer Science, 2021
The reliability of the weather forecast models is a complex issue since it depends on numerous parameters and the technical infrastructure which supports them. In doing so, there is a need for advanced works oriented towards a better understanding of these models and the analysis of main associated parameters. Our approach is to study the applicability
Lassana Coulibaly, Bernard Kamsu-Foguem, Fana Tangara   +2 more
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Transductive learning to rank using association rules

Expert Systems with Applications, 2011
Learning to rank, a task to learn ranking functions to sort a set of entities using machine learning techniques, has recently attracted much interest in information retrieval and machine learning research. However, most of the existing work conducts a supervised learning fashion.
Yan Pan, Haixia Luo, Hongrui Qi, Yong Tang   +3 more
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A learning rule for fuzzy associative memories

Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94), 2002
In this paper, a learning rule for multiple pattern pairs in fuzzy associative memories (FAMs) with max-min composition units is presented. Under a certain condition, the proposed rule can efficiently encode multiple fuzzy pattern pairs in a single FAM and perfect association of these pairs can be achieved.
null Fan Junbo, null Jin Fan, null Shi Yan   +2 more
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Sampling learning based association rules mining algorithm

2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI), 2012
The view that sampling technology could improve the efficiency of data mining significantly has been widely accepted by the research community. The key to sample in data mining is how to design a sampling strategy to get a favorable sample to execute the mining algorithm at minor cost of accuracy.
Xiaoying Xie, Ying Zhang, Yingtao Xu
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Association rule learning in neuropsychological data analysis for Alzheimer’s disease

Journal of Neuropsychology, 2021
Efficient methods of analysis readily available for clinicians continue to be limited within neuropsychological assessment at the raw data level. Here, a novel approach for generating predictive response patterns and analysing neuropsychological raw data is offered.
Keith A, Happawana, Bruce J, Diamond
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Role of Rules in Paired-Associate Learning

Psychological Reports, 1979
14 students in each of four groups learned a single unmixed list of 19 CVC pairs for 12 anticipation trials followed by a free recall of the pairs. In three of the four lists a single rule applied to all of the pairs. The rule was that the words in each pair changed first letter (rhymed), changed middle letter, or changed last letter.
May F. D'amato, Mark Diamond
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Learning Association Rules for Pharmacogenomic Studies

2018
The better understanding of variants of the genomes may improve the knowledge on the causes of the individuals’ different responses to drugs. The Affymetrix DMET (Drug Metabolizing Enzymes and Transporters) microarray platform offers the possibility to determine the gene variants of a patient and correlate them with drug-dependent adverse events.
Giuseppe Agapito, Pietro H. Guzzi, Mario Cannataro   +2 more
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Improving Leung's bidirectional learning rule for associative memories

IEEE Transactions on Neural Networks, 2001
Leung (1994) introduced a perceptron-like learning rule to enhance the recall performance of bidirectional associative memories (BAMs). He proved that his so-called bidirectional learning scheme always yields a solution within a finite number of learning iterations in case that a solution exists.
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