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» A Classifier Ensemble Based on Performance Level Estimation
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KDD
2003
ACM
148views Data Mining» more  KDD 2003»
14 years 7 months ago
Mining concept-drifting data streams using ensemble classifiers
Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud...
Haixun Wang, Wei Fan, Philip S. Yu, Jiawei Han
ISMIR
2004
Springer
204views Music» more  ISMIR 2004»
14 years 26 days ago
Automatic Genre Classification Using Large High-Level Musical Feature Sets
This paper presents a system that extracts 109 musical features from symbolic recordings (MIDI, in this case) and uses them to classify the recordings by genre. The features used ...
Cory McKay, Ichiro Fujinaga
MCS
2005
Springer
14 years 29 days ago
Ensemble Confidence Estimates Posterior Probability
We have previously introduced the Learn++ algorithm that provides surprisingly promising performance for incremental learning as well as data fusion applications. In this contribut...
Michael Muhlbaier, Apostolos Topalis, Robi Polikar
CEC
2007
IEEE
14 years 1 months ago
Evolutionary random neural ensembles based on negative correlation learning
— This paper proposes to incorporate bootstrap of data, random feature subspace and evolutionary algorithm with negative correlation learning to automatically design accurate and...
Huanhuan Chen, Xin Yao
CMSB
2004
Springer
14 years 26 days ago
Modelling Metabolic Pathways Using Stochastic Logic Programs-Based Ensemble Methods
In this paper we present a methodology to estimate rates of enzymatic reactions in metabolic pathways. Our methodology is based on applying stochastic logic learning in ensemble le...
Huma Lodhi, Stephen Muggleton