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» Ensemble Methods in Machine Learning
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PREMI
2007
Springer
14 years 1 months ago
Ensemble Approaches of Support Vector Machines for Multiclass Classification
Support vector machine (SVM) which was originally designed for binary classification has achieved superior performance in various classification problems. In order to extend it to ...
Jun-Ki Min, Jin-Hyuk Hong, Sung-Bae Cho
ICPR
2006
IEEE
14 years 8 months ago
Hybrid Kernel Machine Ensemble for Imbalanced Data Sets
A two-class imbalanced data problem (IDP) emerges when the data from majority class are compactly clustered and the data from minority class are scattered. Though a discriminative...
Kap Luk Chan, Peng Li, Wen Fang
NIPS
2001
13 years 9 months ago
On the Convergence of Leveraging
We give an unified convergence analysis of ensemble learning methods including e.g. AdaBoost, Logistic Regression and the Least-SquareBoost algorithm for regression. These methods...
Gunnar Rätsch, Sebastian Mika, Manfred K. War...
ICPR
2004
IEEE
14 years 8 months ago
Group-based Relevance Feedback with Support Vector Machine Ensembles
Support vector machines (SVMs) have become one of the most promising techniques for relevance feedback in content-based image retrieval (CBIR). Typical SVM-based relevance feedbac...
Chu-Hong Hoi, Michael R. Lyu
ICDM
2003
IEEE
181views Data Mining» more  ICDM 2003»
14 years 1 months ago
Dynamic Weighted Majority: A New Ensemble Method for Tracking Concept Drift
Algorithms for tracking concept drift are important for many applications. We present a general method based on the Weighted Majority algorithm for using any online learner for co...
Jeremy Z. Kolter, Marcus A. Maloof