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» Mining Several Data Bases with an Ensemble of Classifiers
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ICML
2008
IEEE
14 years 8 months ago
Composite kernel learning
The Support Vector Machine (SVM) is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Mul...
Marie Szafranski, Yves Grandvalet, Alain Rakotomam...
MCS
2009
Springer
14 years 11 days ago
Incremental Learning of Variable Rate Concept Drift
We have recently introduced an incremental learning algorithm, Learn++ .NSE, for Non-Stationary Environments, where the data distribution changes over time due to concept drift. Le...
Ryan Elwell, Robi Polikar
ADMI
2010
Springer
13 years 9 months ago
Clustering in a Multi-Agent Data Mining Environment
A Multi-Agent based approach to clustering using a generic Multi-Agent Data Mining (MADM) framework is described. The process use a collection of agents, running several different ...
Santhana Chaimontree, Katie Atkinson, Frans Coenen
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
2010
161views more  BMCBI 2010»
13 years 5 months ago
Addressing the Challenge of Defining Valid Proteomic Biomarkers and Classifiers
Background: The purpose of this manuscript is to provide, based on an extensive analysis of a proteomic data set, suggestions for proper statistical analysis for the discovery of ...
Mohammed Dakna, Keith Harris, Alexandros Kalousis,...