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AffinitySEEKER

       The task of this system is leading learning In­sta­nce Base Learning method. Therefore, the classification of an unknown case relies on calculation of distances between the point (in n-dimensional feature space) that represents the unknown case, and all reference cases stored in the database.

       System has implemented the following distance metrics: Blajdo-Hippe, City_Block, Euclidean, Hamming’s, Mahalanobis, Minkowski’s, Tanimoto’s, Combined and Symbolic. AffinitySEEKER automatic classify  an unknown case using one or all implemented metric. Additionally AffinitySEEKER has implemented very powerful optimization techniques are applied to seek the best selection of control parameters for the development of the learning model. This optimized model is then used for further reference and speeding up processing of the same and/or similar database.