Prototype selection algorithms for distributed learning

DOI10.1016/j.patcog.2010.01.006zbMath1192.68510OpenAlexW1984862487MaRDI QIDQ962819

Ireneusz Czarnowski

Publication date: 7 April 2010

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2010.01.006

zbMATH Keywords

data reductiondistributed learningdistributed data mininginstance selection

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Related Items (5)

Analysis and upscaling of a reactive transport model in fractured porous media with nonlinear transmission condition ⋮ Distributed cooperative learning over time-varying random networks using a gossip-based communication protocol ⋮ Application of agent-based simulated annealing and tabu search procedures to solving the data reduction problem ⋮ Pore-scale modeling and simulation of flow, transport, and adsorptive or osmotic effects in membranes: the influence of membrane microstructure ⋮ A priori error estimate of a multiscale finite element method for transport modeling

Uses Software

• UCI-ml
• Genocop
• C4.5

Cites Work

• Using simulated annealing to optimize the feature selection problem in marketing applications
• Reduction techniques for instance-based learning algorithms
• Introduction to Information Retrieval
• Tabu Search—Part II
• An Experiment with the Edited Nearest-Neighbor Rule
• Nearest prototype classifier designs: An experimental study
• A Framework for Learning from Distributed Data Using Sufficient Statistics and Its Application to Learning Decision Trees
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