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119
AFormal and Computational Properties of the Confidence Boost of Association Rules
"... Some existing notions of redundancy among association rules allow for a logical-style characterization and lead to irredundant bases of absolutely minimum size. One can push the intuition of redundancy further and find an intuitive notion of interest of an association rule, in terms of its “novelty ..."
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, in certain cases, rules of negative correlation may pass the confidence bound. We analyze the properties of two versions of the notion of confidence boost, one of them a natural generalization of the other. We develop efficient algorithmics to filter rules according to their confidence boost, compare
Formal and Computational Properties of the Confidence Boost in Association Rules ∗
, 2010
"... Confidence is a very natural notion to prune and rank the output of an association rule mining algorithm; however, it is well-known that merely imposing absolute confidence and support thresholds leads to certain shortcomings. Many proposals have been suggested as attempts to overcome these shortcom ..."
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Cited by 3 (2 self)
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these shortcomings. Here we propose a different alternative: to complement the association rule mining process by filtering also the obtained rules according to their novelty, measured in a relative way with respect to the confidences of related rules. Our proposal, the confidence boost of a rule, encompasses two
Workshop on Applications of Pattern Analysis Closure-Based Confidence Boost in Association Rules
"... We focus on association rule mining. It is well-known that naive miners end up often providing far too large amounts of mined associations to result actually useful in practice. Many proposals exist for selecting appropriate association rules, trying to measure their interest in various ways; most o ..."
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of the interest of association rules in terms of their “novelty ” with respect to other rules. An irredundant rule is so because its confidence is higher than what the rest of the rules would suggest; then, one can ask: how much higher? Among several variants, a recently proposed parameter, the confidence boost
Indicators for Social and Economic Coping Capacity - Moving Toward a Working Definition of Adaptive Capacity”, Wesleyan-CMU Working Paper.
, 2001
"... Abstract This paper offers a practically motivated method for evaluating systems' abilities to handle external stress. The method is designed to assess the potential contributions of various adaptation options to improving systems' coping capacities by focusing attention directly on the u ..."
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Cited by 109 (14 self)
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-spreading processes (Determinant 6) should be largely functions of macro-scale structures and rules; but they could again take different forms from location to location and option to option. Property rights may be well defined through national institutions, and they may be the basis of private insurance markets
MCS diversity and classifier confidence: A Bayesian approach
"... Bayes' rule is introduced as a coherent averaging strategy for multiclassifier system (MCS) output, and as a strategy for eliminating the uncertainty associated with a particular choice of classifier-model parameters. We use a Markov-Chain Monte Carlo method for efficient selection of classifie ..."
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Cited by 2 (2 self)
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Bayes' rule is introduced as a coherent averaging strategy for multiclassifier system (MCS) output, and as a strategy for eliminating the uncertainty associated with a particular choice of classifier-model parameters. We use a Markov-Chain Monte Carlo method for efficient selection
A Novel Method of Interestingness Measures for Association Rules Mining Based on Profit
"... Association rules mining is an important topic in the domain of data mining and knowledge discovering. Some papers have presented several interestingness measure methods; the most typical are Support, Confidence, Lift, Improve, and so forth. But their limitations are obvious, like no objective crit ..."
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criterion, lack of statistical base, disability of defining negative relationship, and so forth. This paper proposes three new methods, Bi-lift, Bi-improve, and Bi-confidence, for Lift, Improve, and Confidence, respectively. Then, on the basis of utility function and the executing cost of rules, we propose
A Theoretical Approach for Augmenting Association Rule Mining to Predict Protein-Protein Interaction
"... Abstract — Background:Every biological process occurring within the living body involves the formation of protein complexes. Interactions between proteins are an important protein feature. Therefore, determining protein interaction has become one of the most significant problems in the post genomic ..."
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era. Methodology:For effectively determining the interactions occurring among proteins computational approaches like association rule mining could be used. But, only support and confidence measures used with association rule mining can be insufficient at filtering out interesting rules, because
D.Raghu,
"... Positive and negative association rules are important to find useful information hided in massive datasets, especially negative association rules can reflect mutually exclusive correlation among items. Despite a great deal of research, a number of challenges still exist in mining positive and negati ..."
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threshold. In addition to finding confident positive rules that have a strong correlation, the algorithm discovers negative association rules with strong negative correlation between the antecedents and consequents. And we implement the performance evaluated on the basis of time and space complexity
mirWIP: microRNA target prediction based on microRNA-containing ribonucleoprotein-enriched transcripts.
- Nat. Methods.
, 2008
"... Target prediction for animal microRNAs (miRNAs) has been hindered by the small number of verified targets available to evaluate the accuracy of predicted miRNA-target interactions. Recently, a dataset of 3,404 miRNA-associated mRNA transcripts was identified by immunoprecipitation of the RNA-induce ..."
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Cited by 45 (5 self)
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and C. briggsae. We filtered this initial set of raw miRNA target matches on the basis of minimal free energy, phylogenetic conservation and seed pairing configuration (Supplementary Methods and 5¢ seed match features enriched in AIN-IP transcripts Extensive 5¢ seed pairing shows the best enrichment
Comparing Expert and Metric-Based Assessments of
"... In association rule mining, interestingness refers to metrics that are applied to select association rules, beyond support and confidence. For example, Merceron & Yacef (2008) recommend that researchers use a combination of lift and cosine to select association rules, after first filtering out r ..."
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In association rule mining, interestingness refers to metrics that are applied to select association rules, beyond support and confidence. For example, Merceron & Yacef (2008) recommend that researchers use a combination of lift and cosine to select association rules, after first filtering out
Results 1 - 10
of
119