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KDD
2006
ACM
153views Data Mining» more  KDD 2006»
16 years 7 days ago
Semi-supervised time series classification
The problem of time series classification has attracted great interest in the last decade. However current research assumes the existence of large amounts of labeled training data...
Li Wei, Eamonn J. Keogh
KDD
1994
ACM
123views Data Mining» more  KDD 1994»
15 years 3 months ago
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data
We describe scoring metrics for learning Bayesian networks from a combination of user knowledge and statistical data. We identify two important properties of metrics, which we cal...
David Heckerman, Dan Geiger, David Maxwell Chicker...
SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
15 years 1 months ago
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Ashok N. Srivastava
IADIS
2008
15 years 1 months ago
Ontology In Association Rules Pre-Processing And Post-Processing
Data mining has emerged to address the problem of transforming data into useful knowledge. Although most data mining techniques, such as Association Rules, substantially reduce th...
Inhaúma Neves Ferraz, Ana Cristina Bicharra...
ICDE
2006
IEEE
152views Database» more  ICDE 2006»
16 years 1 months ago
Mining Actionable Patterns by Role Models
Data mining promises to discover valid and potentially useful patterns in data. Often, discovered patterns are not useful to the user. "Actionability" addresses this pro...
Ke Wang, Yuelong Jiang, Alexander Tuzhilin