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Data Mining Applications Using Artificial Adaptive Systems electronic resource edited by William J. Tastle.

By: Tastle, William J [editor.]Contributor(s): SpringerLink (Online service)Material type: TextTextPublication details: New York, NY : Springer New York : Imprint: Springer, 2013Description: VII, 275 p. 135 illus., 111 illus. in color. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781461442233Subject(s): Computer Science | Data structures (Computer science) | Data mining | Artificial intelligence | Biometrics | Computer Science | Artificial Intelligence (incl. Robotics) | Data Mining and Knowledge Discovery | Data Structures | BiometricsDDC classification: 006.3 LOC classification: Q334-342TJ210.2-211.495Online resources: Click here to access online
Contents:
Assessing Post-Radiotherapy Treatment involving Brain Volume Differences in Children -- J-Net: an Adaptive System for Computer-Aided Diagnosis in Lung Nodule Characterization -- Population Algorithm: A New Method of Multi-Dimensional Scaling -- Semantics of Point Spaces through the Topological Weighted Centroid and Other Mathematical Quantities -- Meta Net: A New Meta-Classifier Family -- Optimal Informational Sorting: The ACS-ULA Approach -- GUACAMOLE: A New Paradigm for Unsupervised Competitive Learning -- Spatiotemporal Mining: A Systematic Approach to Discrete Diffusion Models for Time and Space Extrapolation.
In: Springer eBooksSummary: none
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Assessing Post-Radiotherapy Treatment involving Brain Volume Differences in Children -- J-Net: an Adaptive System for Computer-Aided Diagnosis in Lung Nodule Characterization -- Population Algorithm: A New Method of Multi-Dimensional Scaling -- Semantics of Point Spaces through the Topological Weighted Centroid and Other Mathematical Quantities -- Meta Net: A New Meta-Classifier Family -- Optimal Informational Sorting: The ACS-ULA Approach -- GUACAMOLE: A New Paradigm for Unsupervised Competitive Learning -- Spatiotemporal Mining: A Systematic Approach to Discrete Diffusion Models for Time and Space Extrapolation.

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