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» Inductive Learning in Less Than One Sequential Data Scan
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KELSI
2004
Springer
13 years 10 months ago
Improving Rule Induction Precision for Automated Annotation by Balancing Skewed Data Sets
There is an overwhelming increase in submissions to genomic databases, posing a problem for database maintenance, especially regarding annotation of fields left blank during submi...
Gustavo E. A. P. A. Batista, Maria Carolina Monard...
CP
2009
Springer
14 years 5 months ago
Minimising Decision Tree Size as Combinatorial Optimisation
Decision tree induction techniques attempt to find small trees that fit a training set of data. This preference for smaller trees, which provides a learning bias, is often justifie...
Christian Bessiere, Emmanuel Hebrard, Barry O'Sull...
KDD
2002
ACM
171views Data Mining» more  KDD 2002»
14 years 5 months ago
Mining complex models from arbitrarily large databases in constant time
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
Geoff Hulten, Pedro Domingos
SAC
2006
ACM
13 years 11 months ago
The impact of sample reduction on PCA-based feature extraction for supervised learning
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal