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Titlebook: Data Mining Applications Using Artificial Adaptive Systems; William J. Tastle Book 2013 Springer Science+Business Media New York 2013 Data

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J-Net: An Adaptive System for Computer-Aided Diagnosis in Lung Nodule Characterization,earning Quantization (AVQ) and Meta-Consensus, two new supervised ANNs, experts in rapid classification and not sensitive to over fitting. After optimization of the distribution of cases among the training and testing sets the following results are achieved: sensitivity (recognition of malignant nod
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Semantics of Point Spaces Through the Topological Weighted Centroid and Other Mathematical Quantitire based on a poorly understood underlying data system. Two kinds of problems, based on the degree of spatialization, are addressed: the first kind of problem possesses an inherent spatial semantic in which all of the relevant characteristics of the observed entities are of a spatial nature; the oth
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GUACAMOLE: A New Paradigm for Unsupervised Competitive Learning,at this particular type of unsupervised learning can provide the basis for a new paradigm where unsupervised learning is taken as the natural reference and in which contexts where supervised learning was commonly believed to be the reference option.
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Spatiotemporal Mining: A Systematic Approach to Discrete Diffusion Models for Time and Space Extrap also carry out analyses by means of static analytical tools such as the Topological Weighted Centroid (TWC) and the Harmonic Center and we find that, overall, the whole suite of techniques is able to provide a fine-grained characterization of the main features of the diffusion process. We consider
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Assessing Post-Radiotherapy Treatment Involving Brain Volume Differences in Children: An Applicatioment for tumors in an effort to identify relationships that might yield knowledge in preventing brain volume loss in future treatments. Analysis of the pre- and post-treatment data is performed first using traditional statistics and then with the assistance of a new kind of artificial adaptive syste
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Population Algorithm: A New Method of Multi-Dimensional Scaling,y on the calculation of a local fitness. Population is not bound to a specific cost function; it is possible to define itself by means of its relation to a considered objective. The motivation for its creation was for use in the elaboration of datasets of great dimension. In performance comparisons
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