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» Data Mining: Machine Learning, Statistics, and Databases
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KDD
2003
ACM
175views Data Mining» more  KDD 2003»
16 years 2 months ago
Time and sample efficient discovery of Markov blankets and direct causal relations
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
Ioannis Tsamardinos, Constantin F. Aliferis, Alexa...
88
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KDD
2009
ACM
172views Data Mining» more  KDD 2009»
15 years 6 months ago
Learning dynamic temporal graphs for oil-production equipment monitoring system
Learning temporal graph structures from time series data reveals important dependency relationships between current observations and histories. Most previous work focuses on learn...
Yan Liu, Jayant R. Kalagnanam, Oivind Johnsen
PKDD
2009
Springer
148views Data Mining» more  PKDD 2009»
15 years 8 months ago
Feature Selection by Transfer Learning with Linear Regularized Models
Abstract. This paper presents a novel feature selection method for classification of high dimensional data, such as those produced by microarrays. It includes a partial supervisio...
Thibault Helleputte, Pierre Dupont
AUSAI
2010
Springer
15 years 21 days ago
Database Normalization as a By-product of Minimum Message Length Inference
Database normalization is a central part of database design in which we re-organise the data stored so as to progressively ensure that as few anomalies occur as possible upon inser...
David L. Dowe, Nayyar Abbas Zaidi
WEBI
2009
Springer
15 years 8 months ago
Learning Deep Web Crawling with Diverse Features
—The key to Deep Web crawling is to submit promising keywords to query form and retrieve Deep Web content efficiently. To select keywords, existing methods make a decision based ...
Lu Jiang, Zhaohui Wu, Qinghua Zheng, Jun Liu