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» Evaluating learning algorithms and classifiers
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ICPR
2008
IEEE
16 years 5 months ago
Prototype learning with margin-based conditional log-likelihood loss
The classification performance of nearest prototype classifiers largely relies on the prototype learning algorithms, such as the learning vector quantization (LVQ) and the minimum...
Cheng-Lin Liu, Xiaobo Jin, Xinwen Hou
FUIN
2002
132views more  FUIN 2002»
15 years 3 months ago
RIONA: A New Classification System Combining Rule Induction and Instance-Based Learning
The article describes a method combining two widely-used empirical approaches to learning from examples: rule induction and instance-based learning. In our algorithm (RIONA) decisi...
Grzegorz Góra, Arkadiusz Wojna
ECCV
2008
Springer
16 years 6 months ago
Face Alignment Via Component-Based Discriminative Search
In this paper, we propose a component-based discriminative approach for face alignment without requiring initialization1 . Unlike many approaches which locally optimize in a small ...
Lin Liang, Rong Xiao, Fang Wen, Jian Sun
EPS
1995
Springer
15 years 7 months ago
PANIC: A Parallel Evolutionary Rule Based System
PANIC (Parallelism And Neural networks In Classifier systems) is a parallel system to evolve behavioral strategies codified by sets of rules. It integrates several adaptive techni...
Antonella Giani, Fabrizio Baiardi, Antonina Starit...
159
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AAAI
1996
15 years 5 months ago
Building Classifiers Using Bayesian Networks
Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with strong assumptions of independence among features, called naive Bayes, is competit...
Nir Friedman, Moisés Goldszmidt