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SOFTWARE
2002
15 years 6 months ago
Temporal Probabilistic Concepts from Heterogeneous Data Sequences
We consider the problem of characterisation of sequences of heterogeneous symbolic data that arise from a common underlying temporal pattern. The data, which are subject to impreci...
Sally I. McClean, Bryan W. Scotney, Fiona Palmer
KDD
2008
ACM
183views Data Mining» more  KDD 2008»
16 years 6 months ago
A bayesian mixture model with linear regression mixing proportions
Classic mixture models assume that the prevalence of the various mixture components is fixed and does not vary over time. This presents problems for applications where the goal is...
Xiuyao Song, Chris Jermaine, Sanjay Ranka, John Gu...
KDD
2006
ACM
176views Data Mining» more  KDD 2006»
16 years 6 months ago
A framework for analysis of dynamic social networks
Finding patterns of social interaction within a population has wide-ranging applications including: disease modeling, cultural and information transmission, and behavioral ecology...
Tanya Y. Berger-Wolf, Jared Saia
KDD
2006
ACM
153views Data Mining» more  KDD 2006»
16 years 6 months ago
Model compression
Often the best performing supervised learning models are ensembles of hundreds or thousands of base-level classifiers. Unfortunately, the space required to store this many classif...
Cristian Bucila, Rich Caruana, Alexandru Niculescu...
KDD
2004
ACM
103views Data Mining» more  KDD 2004»
16 years 6 months ago
An objective evaluation criterion for clustering
We propose and test an objective criterion for evaluation of clustering performance: How well does a clustering algorithm run on unlabeled data aid a classification algorithm? The...
Arindam Banerjee, John Langford