Zusammenfassung
Mit Hilfe der Mustererkennung können Informationen aus großen Datenmengen automatisch gewonnen werden. Obwohl man sich dessen allgemein bewußt ist, schreckt man doch gewöhnlich vor der Aufgabe zurück, sich mit den entsprechenden Methoden befassen zu müssen, denn es gibt sehr viele davon und eine geeignete Auswahl ist schwer zu treffen. Aus diesem Grund werden in dieser Arbeit die einzelnen Verfahren der Mustererkennung erklärt, deren Vor- und Nachteile diskutiert und eine entsprechende Auswahl geboten.
Summary
Pattern recognition permits to extract information present in large data sets in an automatic way. Many scientists acknowledge this fact but are rebutted by the task of learning to use pattern recognition methods. Indeed, there are many methods available and for the newcomer it is extremely difficult to make a selection. For this reason, the paper starts by explaining the models used in pattern recognition. This is followed by a critical discussion of advantages and disadvantages of the methods and a selection of preferred methods.
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Derde, M.P., Massart, D.L. Extraction of information from large data sets by pattern recognition. Z. Anal. Chem. 313, 484–495 (1982). https://doi.org/10.1007/BF00483536
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DOI: https://doi.org/10.1007/BF00483536