Results 221 to 230 of about 92,800 (264)

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 Hiram Guzzi, Mario Cannataro   +2 more
openaire   +1 more source

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
openaire   +1 more source

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
openaire   +1 more source

An associative model of geometry learning: A modified choice rule.

Journal of Experimental Psychology: Animal Behavior Processes, 2008
In a recent article, the authors (Miller & Shettleworth, 2007) showed how the apparently exceptional features of behavior in geometry learning ("reorientation") experiments can be modeled by assuming that geometric and other features at given locations in an arena are learned competitively as in the Rescorla-Wagner model and that the probability of ...
Noam Y, Miller, Sara J, Shettleworth
openaire   +2 more sources

Learning to rank at query-time using association rules

Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, 2008
Some applications have to present their results in the form of ranked lists. This is the case of many information retrieval applications, in which documents must be sorted according to their relevance to a given query. This has led the interest of the information retrieval community in methods that automatically learn effective ranking functions.
Adriano Veloso, Humberto Mossri de Almeida, Marcos André Gonçalves, Wagner Meira Jr.   +3 more
openaire   +1 more source

Meta-learning for Post-processing of Association Rules

2010
The paper presents a novel approach to post-processing of association rules based on the idea of meta-learning. A subsequent association rule mining step is applied to the results of "standard" association rule mining. We thus obtain "rules about rules" that help to better understand the association rules generated in the first step.
Petr Berka, Jan Rauch
openaire   +1 more source

Learning rule for associative memory in recurrent neural networks

2015 International Joint Conference on Neural Networks (IJCNN), 2015
We present a new learning rule for intralayer connections in neural networks. The rule is based on Hebbian learning principles and is derived from information theoretic considerations. A simple network trained using the rule is shown to have associative memory like properties.
Theju Jacob, Wesley E. Snyder
openaire   +1 more source

Apriori Association Rules Learning

2018
HTTP cookies are used to monitor web-traffic and track users surfing the Internet. We often notice that promotions (ads) on websites tend to match our needs, reveal our prior browsing history, or reflect our interests. That is not an accident. Nowadays, recommendation systems are highly based on machine learning methods that can learn the behavior, e.g.
openaire   +1 more source

Based on the Reinforcement Learning Association Rules Recommendation Study

2009 Fifth International Conference on Semantics, Knowledge and Grid, 2009
Reinforcement learning is an important method of machine learning. This paper using the graph theory to express varieties of knowledge points, which their’s relationship is expressed by the graph of topological graph. Applied the Technology of association rule Recommendation to deal with the relationship between these knowledge points, give the ...
Jinqiao Wang, Qing Yang, Li Zhu, JunLi Sun   +3 more
openaire   +1 more source

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 ...
Peter Dayan, David J. Willshaw
openaire   +4 more sources