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» Identifying Objects Using Cluster and Concept Analysis
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ECML
2006
Springer
15 years 2 months ago
Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Corneliu Henegar, Karine Clément, Jean-Dani...
ICDAR
2003
IEEE
15 years 4 months ago
Unsupervised Feature Selection Using Multi-Objective Genetic Algorithms for Handwritten Word Recognition
In this paper a methodology for feature selection in unsupervised learning is proposed. It makes use of a multiobjective genetic algorithm where the minimization of the number of ...
Marisa E. Morita, Robert Sabourin, Flávio B...
CASCON
2007
106views Education» more  CASCON 2007»
15 years 16 days ago
Identifying active subgroups in online communities
As online communities proliferate, methods are needed to explore and capture patterns of activity within them. This paper focuses on the problem of identifying active subgroups wi...
Alvin Chin, Mark H. Chignell
ICTAI
2008
IEEE
15 years 5 months ago
Knee Point Detection on Bayesian Information Criterion
The main challenge of cluster analysis is that the number of clusters or the number of model parameters is seldom known, and it must therefore be determined before clustering. Bay...
Qinpei Zhao, Mantao Xu, Pasi Fränti
ACSAC
2004
IEEE
15 years 2 months ago
Visualizing and Identifying Intrusion Context from System Calls Trace
Anomaly-based Intrusion Detection (AID) techniques are useful for detecting novel intrusions without known signatures. However, AID techniques suffer from higher false alarm rate ...
Zhuowei Li, Amitabha Das