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FLAIRS
2004
14 years 11 months ago
Clustering Spatial Data in the Presence of Obstacles
Clustering is a form of unsupervised machine learning. In this paper, we proposed the DBRS_O method to identify clusters in the presence of intersected obstacles. Without doing an...
Xin Wang, Howard J. Hamilton
ISCAS
2006
IEEE
143views Hardware» more  ISCAS 2006»
15 years 3 months ago
Dynamic computation in a recurrent network of heterogeneous silicon neurons
Abstract—We describe a neuromorphic chip with a twolayer excitatory-inhibitory recurrent network of spiking neurons that exhibits localized clusters of neural activity. Unlike ot...
Paul Merolla, Kwabena Boahen
CVPR
2009
IEEE
16 years 4 months ago
Learning Trajectory Patterns by Clustering: Experimental Studies and Comparative Evaluation
Recently a large amount of research has been devoted to automatic activity analysis. Typically, activities have been defined by their motion characteristics and represented by t...
Brendan Morris, Mohan M. Trivedi
SNPD
2010
14 years 11 months ago
Explaining Classification by Finding Response-Related Subgroups in Data
Abstract--A method for explaining results of a regressionbased classifier is proposed. The data is clustered using a metric extracted from the classifier. This way, clusters found ...
Elina Parviainen, Aki Vehtari
BMCBI
2006
164views more  BMCBI 2006»
14 years 9 months ago
Evaluation of clustering algorithms for gene expression data
Background: Cluster analysis is an integral part of high dimensional data analysis. In the context of large scale gene expression data, a filtered set of genes are grouped togethe...
Susmita Datta, Somnath Datta