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Nonmetric clustering: new approaches for ecological data
Conference on Artificial Intelligence for Applications (1994)
  • Geoffrey Matthews, Western Washington University
  • Robin Matthews, Western Washington University
  • Wayne Landis, Western Washington University
Ecological studies and multispecies ecotoxicological tests are based on the examination of a variety of physical, chemical and biological data with the intent of finding patterns in their changing relationships over time. The data sets resulting from such studies are often noisy, incomplete, and difficult to envision. We have developed machine learning and visualization software to aid in the analysis, modelling, and understanding of such systems. The software is based on nonmetric conceptual clustering, which attempts to analyze the data into clusters that are strongly associated with several measured parameters. Our analysis and visualization tools not only confirmed suspected ecological patterns, but revealed aspects of the data that were unnoticed by ecologists using conventional statistical techniques.
  • Nonmetric conceptual clustering,
  • Ecological patterns
Publication Date
San Antonio, TX
Citation Information
Geoffrey Matthews, Robin Matthews and Wayne Landis. "Nonmetric clustering: new approaches for ecological data" Conference on Artificial Intelligence for Applications (1994)
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