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» A statistical approach to rule learning
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SDM
2009
SIAM
154views Data Mining» more  SDM 2009»
14 years 7 months ago
AMORI: A Metric-Based One Rule Inducer.
The requirements of real-world data mining problems vary extensively. It is plausible to assume that some of these requirements can be expressed as application-specific performan...
Niklas Lavesson, Paul Davidsson
BMCBI
2008
98views more  BMCBI 2008»
13 years 10 months ago
GBNet: Deciphering regulatory rules in the co-regulated genes using a Gibbs sampler enhanced Bayesian network approach
Background: Combinatorial regulation of transcription factors (TFs) is important in determining the complex gene expression patterns particularly in higher organisms. Deciphering ...
Li Shen, Jie Liu, Wei Wang
AAAI
2008
14 years 10 days ago
Examining Difficulties Software Developers Encounter in the Adoption of Statistical Machine Learning
Statistical machine learning continues to show promise as a tool for addressing complex problems in a variety of domains. An increasing number of developers are therefore looking ...
Kayur Patel, James Fogarty, James A. Landay, Bever...
DSMML
2004
Springer
14 years 3 months ago
SVM Based Learning System for Information Extraction
Abstract. We present an SVM-based learning algorithm for information extraction, including experiments on the influence of different algorithm settings. Our approach needs fewer ...
Yaoyong Li, Kalina Bontcheva, Hamish Cunningham
ICANN
2003
Springer
14 years 3 months ago
Optimal Hebbian Learning: A Probabilistic Point of View
Many activity dependent learning rules have been proposed in order to model long-term potentiation (LTP). Our aim is to derive a spike time dependent learning rule from a probabili...
Jean-Pascal Pfister, David Barber, Wulfram Gerstne...