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» A statistical approach to rule learning
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NAACL
2007
13 years 11 months ago
A Cascaded Machine Learning Approach to Interpreting Temporal Expressions
A new architecture for identifying and interpreting temporal expressions is introduced, in which the large set of complex hand-crafted rules standard in systems for this task is r...
David Ahn, Joris van Rantwijk, Maarten de Rijke
SDM
2009
SIAM
123views Data Mining» more  SDM 2009»
14 years 7 months ago
Measuring Discrimination in Socially-Sensitive Decision Records.
Discrimination in social sense (e.g., against minorities and disadvantaged groups) is the subject of many laws worldwide, and it has been extensively studied in the social and eco...
Dino Pedreschi, Franco Turini, Salvatore Ruggieri
ECAI
2004
Springer
14 years 3 months ago
Exploiting Association and Correlation Rules - Parameters for Improving the K2 Algorithm
A Bayesian network is an appropriate tool to deal with the uncertainty that is typical of real-life applications. Bayesian network arcs represent statistical dependence between dif...
Evelina Lamma, Fabrizio Riguzzi, Sergio Storari
SDM
2004
SIAM
224views Data Mining» more  SDM 2004»
13 years 11 months ago
Hierarchical Clustering for Thematic Browsing and Summarization of Large Sets of Association Rules
In this paper we propose a method for grouping and summarizing large sets of association rules according to the items contained in each rule. We use hierarchical clustering to par...
Alípio Jorge
GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
14 years 3 months ago
A statistical learning theory approach of bloat
Code bloat, the excessive increase of code size, is an important issue in Genetic Programming (GP). This paper proposes a theoretical analysis of code bloat in the framework of sy...
Sylvain Gelly, Olivier Teytaud, Nicolas Bredeche, ...