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» Sequential Inductive Learning
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BMCBI
2008
88views more  BMCBI 2008»
15 years 2 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 7 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
15 years 3 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»
15 years 2 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 8 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