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» Evaluating learning algorithms and classifiers
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APNOMS
2008
Springer
15 years 6 months ago
Application of Data Mining to Network Intrusion Detection: Classifier Selection Model
As network attacks have increased in number and severity over the past few years, intrusion detection system (IDS) is increasingly becoming a critical component to secure the netwo...
Huy Anh Nguyen, Deokjai Choi
EVOW
2008
Springer
15 years 5 months ago
Improving the Performance of Hierarchical Classification with Swarm Intelligence
In this paper we propose a new method to improve the performance of hierarchical classification. We use a swarm intelligence algorithm to select the type of classification algorith...
Nicholas Holden, Alex Alves Freitas
ICML
2007
IEEE
16 years 4 months ago
An empirical evaluation of deep architectures on problems with many factors of variation
Recently, several learning algorithms relying on models with deep architectures have been proposed. Though they have demonstrated impressive performance, to date, they have only b...
Hugo Larochelle, Dumitru Erhan, Aaron C. Courville...
168
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EC
2006
195views ECommerce» more  EC 2006»
15 years 4 months ago
Automated Global Structure Extraction for Effective Local Building Block Processing in XCS
Learning Classifier Systems (LCSs), such as the accuracy-based XCS, evolve distributed problem solutions represented by a population of rules. During evolution, features are speci...
Martin V. Butz, Martin Pelikan, Xavier Llorà...
ICDM
2007
IEEE
131views Data Mining» more  ICDM 2007»
15 years 8 months ago
Predicting and Optimizing Classifier Utility with the Power Law
When data collection is costly and/or takes a significant amount of time, an early prediction of the classifier performance is extremely important for the design of the data minin...
Mark Last