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ML
2000
ACM
144views Machine Learning» more  ML 2000»
15 years 4 months ago
MultiBoosting: A Technique for Combining Boosting and Wagging
MultiBoosting is an extension to the highly successful AdaBoost technique for forming decision committees. MultiBoosting can be viewed as combining AdaBoost with wagging. It is abl...
Geoffrey I. Webb
ICMLC
2010
Springer
15 years 2 months ago
CMAC-based fault accommodation control for tank system
- This paper presents a learning approach using cerebellar model articulation controller (CMAC) to accommodate faults for a class of multivariable nonlinear systems. A CMAC is prop...
Chih-Min Lin, Chang-Chih Chung, Yu-Ju Liu, Daniel ...
ECTEL
2011
Springer
14 years 4 months ago
On the Way to a Science Intelligence: Visualizing TEL Tweets for Trend Detection
This paper presents an adaptable system for detecting trends based on the micro-blogging service Twitter, and sets out to explore to what extent such a tool can support researchers...
Peter Kraker, Claudia Wagner, Fleur Jeanquartier, ...
KDD
2005
ACM
143views Data Mining» more  KDD 2005»
16 years 4 months ago
SVM selective sampling for ranking with application to data retrieval
Learning ranking (or preference) functions has been a major issue in the machine learning community and has produced many applications in information retrieval. SVMs (Support Vect...
Hwanjo Yu
ECML
2005
Springer
15 years 10 months ago
Error-Sensitive Grading for Model Combination
Abstract. Ensemble learning is a powerful learning approach that combines multiple classifiers to improve prediction accuracy. An important decision while using an ensemble of cla...
Surendra K. Singhi, Huan Liu