Pudil, Pavel; Novovičová, Jana; Bláha, Svatopluk Statistical approach to pattern recognition. Theory and practical solution by means of PREDITAS system. (English) Zbl 0752.68070 Kybernetika 27, Suppl. No. 1-6, 78 pp. (1991). The classification is treated as the primary goal of pattern recognition. There is a number of related problems requiring careful attention when solving problems from real life: evaluation of the training set quality, feature selection and dimensionality reduction, estimation of classification error, iterative corrections of individual phases of the solution according to the results of testing, and finally the problem of interconnecting feature selection with the classifier design as much as possible. An attempt to provide a complex solution of all these interconnected problems has resulted in the design of PREDITAS (Pattern REcognition and DIagnostic TAsk Solver) software package. It is a combination of both theoretically based and heuristic procedures, incorporating as much as possible requirements and suggestions of specialists from various application fields. Theoretical background of the employed methods and algorithms, together with their reasoning and some examples of applications is presented. Reviewer: G.Stanke (Berlin) MSC: 68T10 Pattern recognition, speech recognition 62H30 Classification and discrimination; cluster analysis (statistical aspects) Keywords:statistical pattern classification; Bayes rule; linear classification; searching methods; feature selection Software:PREDITAS PDF BibTeX XML Full Text: EuDML References:  T. W. Anderson: An Introduction to Multivariate Statistical Analysis. John Wiley, New York 1958. · Zbl 0083.14601  G. Biswas A. K. Jain, R. Dubes: Evaluation of projection algorithms. IEEE Trans. Pattern Anal. Machine Intell. 3 (1981), 701-708.  S. Bláha P. Pudil, R. 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It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.