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» Evaluating learning algorithms and classifiers
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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
IPMI
2001
Springer
16 years 5 months ago
Deformation Analysis for Shape Based Classification
Statistical analysis of anatomical shape differences between two different populations can be reduced to a classification problem, i.e., learning a classifier function for assignin...
Polina Golland, W. Eric L. Grimson, Martha Elizabe...
ML
2006
ACM
15 years 4 months ago
XRules: An effective algorithm for structural classification of XML data
Abstract XML documents have recently become ubiquitous because of their varied applicability in a number of applications. Classification is an important problem in the data mining ...
Mohammed Javeed Zaki, Charu C. Aggarwal
ECCV
2004
Springer
16 years 6 months ago
Weak Hypotheses and Boosting for Generic Object Detection and Recognition
In this paper we describe the first stage of a new learning system for object detection and recognition. For our system we propose Boosting [5] as the underlying learning technique...
Andreas Opelt, Michael Fussenegger, Axel Pinz, Pet...
SIGMOD
2010
ACM
213views Database» more  SIGMOD 2010»
15 years 9 months ago
On active learning of record matching packages
We consider the problem of learning a record matching package (classifier) in an active learning setting. In active learning, the learning algorithm picks the set of examples to ...
Arvind Arasu, Michaela Götz, Raghav Kaushik