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» Combining Two Data Mining Methods for System Identification
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BMCBI
2010
178views more  BMCBI 2010»
13 years 7 months ago
Selecting high-dimensional mixed graphical models using minimal AIC or BIC forests
Background: Chow and Liu showed that the maximum likelihood tree for multivariate discrete distributions may be found using a maximum weight spanning tree algorithm, for example K...
David Edwards, Gabriel C. G. de Abreu, Rodrigo Lab...
KDD
2005
ACM
127views Data Mining» more  KDD 2005»
14 years 8 months ago
Detection of emerging space-time clusters
We propose a new class of spatio-temporal cluster detection methods designed for the rapid detection of emerging space-time clusters. We focus on the motivating application of pro...
Daniel B. Neill, Andrew W. Moore, Maheshkumar Sabh...
COMPGEOM
2005
ACM
13 years 9 months ago
The skip quadtree: a simple dynamic data structure for multidimensional data
We present a new multi-dimensional data structure, which we call the skip quadtree (for point data in R2) or the skip octree (for point data in Rd, with constant d > 2). Our da...
David Eppstein, Michael T. Goodrich, Jonathan Z. S...
CVPR
2008
IEEE
14 years 9 months ago
Constrained spectral clustering through affinity propagation
Pairwise constraints specify whether or not two samples should be in one cluster. Although it has been successful to incorporate them into traditional clustering methods, such as ...
Miguel Á. Carreira-Perpiñán, ...
KDD
2002
ACM
147views Data Mining» more  KDD 2002»
14 years 8 months ago
Visualized Classification of Multiple Sample Types
The goal of the knowledge discovery and data mining is to extract the useful knowledge from the given data. Visualization enables us to find structures, features, patterns, and re...
Li Zhang, Aidong Zhang, Murali Ramanathan