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» Adapting classification rule induction to subgroup discovery
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ILP
2003
Springer
15 years 11 months ago
ILP for Mathematical Discovery
We believe that AI programs written for discovery tasks will need to simultaneously employ a variety of reasoning techniques such as induction, abduction, deduction, calculation an...
Simon Colton, Stephen Muggleton
ECAI
2004
Springer
15 years 9 months ago
Avoiding Data Overfitting in Scientific Discovery: Experiments in Functional Genomics
Functional genomics is a typical scientific discovery domain characterized by a very large number of attributes (genes) relative to the number of examples (observations). The dang...
Dragan Gamberger, Nada Lavrac
KDD
1995
ACM
99views Data Mining» more  KDD 1995»
15 years 9 months ago
Knowledge Discovery in a Water Quality Database
Weapply rule induction to mine for knowledgein a database which stores data obtained by monitoring the water quality of the rivers in Slovenia. The database contains measurementda...
Saso Dzeroski
EDBT
2000
ACM
15 years 9 months ago
Mining Classification Rules from Datasets with Large Number of Many-Valued Attributes
Decision tree induction algorithms scale well to large datasets for their univariate and divide-and-conquer approach. However, they may fail in discovering effective knowledge when...
Giovanni Giuffrida, Wesley W. Chu, Dominique M. Ha...
GECCO
2007
Springer
481views Optimization» more  GECCO 2007»
15 years 11 months ago
A hybrid PSO/ACO algorithm for classification
In a previous work we have proposed a hybrid Particle Swarm Optimisation/Ant Colony Optimisation (PSO/ACO) algorithm for the discovery of classification rules, in the context of d...
Nicholas Holden, Alex Alves Freitas