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» Sequential Inductive Learning
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BMCBI
2008
88views more  BMCBI 2008»
14 years 10 months ago
Use of machine learning algorithms to classify binary protein sequences as highly-designable or poorly-designable
Background: By using a standard Support Vector Machine (SVM) with a Sequential Minimal Optimization (SMO) method of training, Na
Myron Peto, Andrzej Kloczkowski, Vasant Honavar, R...
ISI
2003
Springer
15 years 3 months ago
Authorship Analysis in Cybercrime Investigation
Criminals have been using the Internet to distribute a wide range of illegal materials globally in an anonymous manner, making criminal identity tracing difficult in the cybercrime...
Rong Zheng, Yi Qin, Zan Huang, Hsinchun Chen
ISMB
1993
14 years 11 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
FUIN
2006
95views more  FUIN 2006»
14 years 10 months ago
Multistrategy Operators for Relational Learning and Their Cooperation
Traditional Machine Learning approaches based on single inference mechanisms have reached their limits. This causes the need for a framework that integrates approaches based on aba...
Floriana Esposito, Nicola Fanizzi, Stefano Ferilli...
IROS
2008
IEEE
113views Robotics» more  IROS 2008»
15 years 4 months ago
Motion recognition and generation by combining reference-point-dependent probabilistic models
— This paper presents a method to recognize and generate sequential motions for object manipulation such as placing one object on another or rotating it. Motions are learned usin...
Komei Sugiura, Naoto Iwahashi