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AUSDM
2007
Springer
173views Data Mining» more  AUSDM 2007»
14 years 2 months ago
The Use of Various Data Mining and Feature Selection Methods in the Analysis of a Population Survey Dataset
This paper reports the results of feature reduction in the analysis of a population based dataset for which there were no specific target variables. All attributes were assessed a...
Ellen Pitt, Richi Nayak
ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
15 years 29 days ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer
ICANN
2001
Springer
14 years 14 days ago
Independent Variable Group Analysis
Humans tend to group together related properties in order to understand complex phenomena. When modeling large problems with limited representational resources, it is important to...
Krista Lagus, Esa Alhoniemi, Harri Valpola
ESWS
2008
Springer
13 years 9 months ago
Instance Based Clustering of Semantic Web Resources
Abstract. The original Semantic Web vision was explicit in the need for intelligent autonomous agents that would represent users and help them navigate the Semantic Web. We argue t...
Gunnar Aastrand Grimnes, Peter Edwards, Alun D. Pr...
KDD
2006
ACM
240views Data Mining» more  KDD 2006»
14 years 8 months ago
Adaptive event detection with time-varying poisson processes
Time-series of count data are generated in many different contexts, such as web access logging, freeway traffic monitoring, and security logs associated with buildings. Since this...
Alexander T. Ihler, Jon Hutchins, Padhraic Smyth