Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1
Search results for: Bernardino Arcayy
1 Hierarchical Clustering Analysis with SOM Networks
Authors: Diego Ordonez, Carlos Dafonte, Minia Manteiga, Bernardino Arcayy
Abstract:
This work presents a neural network model for the clustering analysis of data based on Self Organizing Maps (SOM). The model evolves during the training stage towards a hierarchical structure according to the input requirements. The hierarchical structure symbolizes a specialization tool that provides refinements of the classification process. The structure behaves like a single map with different resolutions depending on the region to analyze. The benefits and performance of the algorithm are discussed in application to the Iris dataset, a classical example for pattern recognition.Keywords: Neural networks, Self-organizing feature maps, Hierarchicalsystems, Pattern clustering methods.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1947