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» Evaluating learning algorithms and classifiers
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112
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ISMB
1993
15 years 1 months ago
Protein Structure Prediction: Selecting Salient Features from Large Candidate Pools
Weintroduce a parallel approach, "DT-SELECT," for selecting features used by inductive learning algorithms to predict protein secondary structure. DT-SELECTis able to ra...
Kevin J. Cherkauer, Jude W. Shavlik
98
Voted
KAIS
2008
165views more  KAIS 2008»
15 years 13 days ago
Multirelational classification: a multiple view approach
Multirelational classification aims at discovering useful patterns across multiple inter-connected tables (relations) in a relational database. Many traditional learning techniques...
Hongyu Guo, Herna L. Viktor
CVPR
2008
IEEE
16 years 2 months ago
Consistent image analogies using semi-supervised learning
In this paper we study the following problem: given two source images A and A , and a target image B, can we learn to synthesize a new image B which relates to B in the same way t...
Li Cheng, S. V. N. Vishwanathan, Xinhua Zhang
EMNLP
2008
15 years 1 months ago
Regular Expression Learning for Information Extraction
Regular expressions have served as the dominant workhorse of practical information extraction for several years. However, there has been little work on reducing the manual effort ...
Yunyao Li, Rajasekar Krishnamurthy, Sriram Raghava...
UAI
2003
15 years 1 months ago
On Local Optima in Learning Bayesian Networks
This paper proposes and evaluates the k-greedy equivalence search algorithm (KES) for learning Bayesian networks (BNs) from complete data. The main characteristic of KES is that i...
Jens D. Nielsen, Tomás Kocka, José M...