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GECCO
2006
Springer
173views Optimization» more  GECCO 2006»
15 years 4 months ago
Pareto-coevolutionary genetic programming classifier
The conversion and extension of the Incremental ParetoCoevolution Archive algorithm (IPCA) into the domain of Genetic Programming classifier evolution is presented. In order to ac...
Michal Lemczyk, Malcolm I. Heywood
103
Voted
ICTAI
2005
IEEE
15 years 6 months ago
ACE: An Aggressive Classifier Ensemble with Error Detection, Correction, and Cleansing
Learning from noisy data is a challenging and reality issue for real-world data mining applications. Common practices include data cleansing, error detection and classifier ensemb...
Yan Zhang, Xingquan Zhu, Xindong Wu, Jeffrey P. Bo...
ICPR
2006
IEEE
16 years 1 months ago
Finding Rule Groups to Classify High Dimensional Gene Expression Datasets
Microarray data provides quantitative information about the transcription profile of cells. To analyze microarray datasets, methodology of machine learning has increasingly attrac...
Jiyuan An, Yi-Ping Phoebe Chen
99
Voted
KDD
2010
ACM
287views Data Mining» more  KDD 2010»
15 years 2 months ago
Designing efficient cascaded classifiers: tradeoff between accuracy and cost
We propose a method to train a cascade of classifiers by simultaneously optimizing all its stages. The approach relies on the idea of optimizing soft cascades. In particular, inst...
Vikas C. Raykar, Balaji Krishnapuram, Shipeng Yu
CVPR
2008
IEEE
16 years 2 months ago
Dynamic visual category learning
Dynamic visual category learning calls for efficient adaptation as new training images become available or new categories are defined, existing training images or categories becom...
Tom Yeh, Trevor Darrell