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JCB
2002
70views more  JCB 2002»
13 years 7 months ago
Strong Feature Sets from Small Samples
For small samples, classi er design algorithms typically suffer from over tting. Given a set of features, a classi er must be designed and its error estimated. For small samples, ...
Seungchan Kim, Edward R. Dougherty, Junior Barrera...
EUMAS
2006
13 years 9 months ago
A Customizable Multi-Agent System for Distributed Data Mining
We present a general Multi-Agent System framework for distributed data mining based on a Peer-toPeer model. The framework adopts message-based asynchronous communication and a dyn...
Giancarlo Fortino, Giuseppe Di Fatta
BMCBI
2008
92views more  BMCBI 2008»
13 years 7 months ago
A semiparametric modeling framework for potential biomarker discovery and the development of metabonomic profiles
Background: The discovery of biomarkers is an important step towards the development of criteria for early diagnosis of disease status. Recently electrospray ionization (ESI) and ...
Samiran Ghosh, David F. Grant, Dipak K. Dey, Denni...
CLUSTER
2005
IEEE
14 years 1 months ago
A pipelined data-parallel algorithm for ILP
The amount of data collected and stored in databases is growing considerably for almost all areas of human activity. Processing this amount of data is very expensive, both humanly...
Nuno A. Fonseca, Fernando M. A. Silva, Víto...
KDD
2006
ACM
164views Data Mining» more  KDD 2006»
14 years 8 months ago
Sampling from large graphs
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
Jure Leskovec, Christos Faloutsos