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» Rule Combination in Inductive Learning
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CSB
2005
IEEE
129views Bioinformatics» more  CSB 2005»
15 years 3 months ago
Rule Clustering and Super-rule Generation for Transmembrane Segments Prediction
The explanation of a decision is important for the acceptance of machine learning technology in bioinformatics applications such as protein structure prediction. In past research,...
Jieyue He, Bernard Chen, Hae-Jin Hu, Robert W. Har...
IJCAI
2003
14 years 11 months ago
Constructing Diverse Classifier Ensembles using Artificial Training Examples
Ensemble methods like bagging and boosting that combine the decisions of multiple hypotheses are some of the strongest existing machine learning methods. The diversity of the memb...
Prem Melville, Raymond J. Mooney
EMNLP
2010
14 years 7 months ago
Incorporating Content Structure into Text Analysis Applications
In this paper, we investigate how modeling content structure can benefit text analysis applications such as extractive summarization and sentiment analysis. This follows the lingu...
Christina Sauper, Aria Haghighi, Regina Barzilay
ECML
2005
Springer
15 years 3 months ago
Mode Directed Path Finding
Abstract. Learning from multi-relational domains has gained increasing attention over the past few years. Inductive logic programming (ILP) systems, which often rely on hill-climbi...
Irene M. Ong, Inês de Castro Dutra, David Pa...
CVPR
2008
IEEE
15 years 11 months ago
Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation and recognition
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...