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» Learning from Multiple Sources of Inaccurate Data
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CIDM
2009
IEEE
15 years 10 months ago
Diversity analysis on imbalanced data sets by using ensemble models
— Many real-world applications have problems when learning from imbalanced data sets, such as medical diagnosis, fraud detection, and text classification. Very few minority clas...
Shuo Wang, Xin Yao
HIS
2004
15 years 4 months ago
K-Ranked Covariance Based Missing Values Estimation for Microarray Data Classification
Microarray data often contains multiple missing genetic expression values that degrade the performance of statistical and machine learning algorithms. This paper presents a K rank...
Muhammad Shoaib B. Sehgal, Iqbal Gondal, Laurence ...
105
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COLING
2000
15 years 4 months ago
Improving SMT quality with morpho-syntactic analysis
In the framework of statistical machine translation (SMT), correspondences between the words in the source and the target language are learned from bilingual corpora on the basis ...
Sonja Nießen, Hermann Ney
136
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AAAI
2004
15 years 4 months ago
Learning and Applying Competitive Strategies
Learning reusable sequences can support the development of expertise in many domains, either by improving decisionmaking quality or decreasing execution speed. This paper introduc...
Esther Lock, Susan L. Epstein
COLT
1992
Springer
15 years 7 months ago
Polynomial Time Inference of a Subclass of Context-Free Transformations
This paper deals with a class of Prolog programs, called context-free term transformations (CFT). We present a polynomial time algorithm to identify a subclass of CFT, whose progr...
Hiroki Arimura, Hiroki Ishizaka, Takeshi Shinohara