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» Finding Groups in Data: Cluster Analysis with Ants
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KDD
2005
ACM
112views Data Mining» more  KDD 2005»
16 years 7 days ago
Model-based overlapping clustering
While the vast majority of clustering algorithms are partitional, many real world datasets have inherently overlapping clusters. Several approaches to finding overlapping clusters...
Arindam Banerjee, Chase Krumpelman, Joydeep Ghosh,...
GECCO
2004
Springer
138views Optimization» more  GECCO 2004»
15 years 5 months ago
Exploratory Data Analysis with Interactive Evolution
We illustrate with two simple examples how Interactive Evolutionary Computation (IEC) can be applied to Exploratory Data Analysis (EDA). IEC is particularly valuable in an EDA cont...
Sergey Malinchik, Eric Bonabeau
BMCBI
2008
143views more  BMCBI 2008»
14 years 12 months ago
Gene identification and protein classification in microbial metagenomic sequence data via incremental clustering
Background: The identification and study of proteins from metagenomic datasets can shed light on the roles and interactions of the source organisms in their communities. However, ...
Shibu Yooseph, Weizhong Li, Granger G. Sutton
CIDU
2010
14 years 9 months ago
Optimal Partitions of Data In Higher Dimensions
Given any collection of data cells in a data space X, consider the problem of finding the optimal partition of the data cells into blocks which are unions of cells. The algorithms...
Bradley W. Jackson, Jeffrey D. Scargle, Chris Cusa...
ENGL
2007
180views more  ENGL 2007»
14 years 11 months ago
Biological Data Mining for Genomic Clustering Using Unsupervised Neural Learning
— The paper aims at designing a scheme for automatic identification of a species from its genome sequence. A set of 64 three-tuple keywords is first generated using the four type...
Shreyas Sen, Seetharam Narasimhan, Amit Konar