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ICML
2004
IEEE
15 years 10 months ago
Large margin hierarchical classification
We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure. This structure is encoded b...
Ofer Dekel, Joseph Keshet, Yoram Singer
100
Voted
JMLR
2010
161views more  JMLR 2010»
14 years 4 months ago
Accuracy-Rejection Curves (ARCs) for Comparing Classification Methods with a Reject Option
Data extracted from microarrays are now considered an important source of knowledge about various diseases. Several studies based on microarray data and the use of receiver operat...
Malik Sajjad Ahmed Nadeem, Jean-Daniel Zucker, Bla...
ML
2002
ACM
145views Machine Learning» more  ML 2002»
14 years 9 months ago
Boosting Methods for Regression
In this paper we examine ensemble methods for regression that leverage or "boost" base regressors by iteratively calling them on modified samples. The most successful lev...
Nigel Duffy, David P. Helmbold
MLDM
2008
Springer
14 years 9 months ago
Classification Based on Consistent Itemset Rules
Abstract. We propose an approach to build a classifier composing consistent (100% confident) rules. Recently, associative classifiers that utilize association rules have been widel...
Yohji Shidara, Mineichi Kudo, Atsuyoshi Nakamura
ECCV
2008
Springer
15 years 11 months ago
Local Regularization for Multiclass Classification Facing Significant Intraclass Variations
We propose a new local learning scheme that is based on the principle of decisiveness: the learned classifier is expected to exhibit large variability in the direction of the test ...
Lior Wolf, Yoni Donner