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» On learning algorithm selection for classification
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JMLR
2006
109views more  JMLR 2006»
15 years 2 months ago
Some Discriminant-Based PAC Algorithms
A classical approach in multi-class pattern classification is the following. Estimate probability distributions that generated the observations for each label class, and then labe...
Paul W. Goldberg
AIEDU
2010
14 years 9 months ago
Scaffolding Meta-Cognitive Skills for Effective Analogical Problem Solving via Tailored Example Selection
Although worked-out examples play a key role in cognitive skill acquisition, research demonstrates that students have various levels of meta-cognitive abilities for using examples ...
Kasia Muldner, Cristina Conati
ICML
2006
IEEE
16 years 3 months ago
Full Bayesian network classifiers
The structure of a Bayesian network (BN) encodes variable independence. Learning the structure of a BN, however, is typically of high computational complexity. In this paper, we e...
Jiang Su, Harry Zhang
102
Voted
AIRS
2008
Springer
15 years 8 months ago
Combining WordNet and ConceptNet for Automatic Query Expansion: A Learning Approach
We present a novel approach that transforms the weighting task to a typical coarse-grained classification problem, aiming to assign appropriate weights for candidate expansion term...
Ming-Hung Hsu, Ming-Feng Tsai, Hsin-Hsi Chen
127
Voted
AUSDM
2008
Springer
211views Data Mining» more  AUSDM 2008»
15 years 4 months ago
LBR-Meta: An Efficient Algorithm for Lazy Bayesian Rules
LBR is a highly accurate classification algorithm, which lazily constructs a single Bayesian rule for each test instance at classification time. However, its computational complex...
Zhipeng Xie