Abstract
Data Analysis can be considered either as “the search for structure in data (J.C. Bezdek and Pal, 1992)or as a way to reduce the complexity of large masses of data. We shall focus in this paper on the second point of view. In order to clarify the terminology of data analysis used throughout this paper a brief description of its general process is given in what follows. In data analysis objects are considered which are described by some attributes. Objects can, for example, be persons, things (machines, products,…), time series, sensor signals, process states, and so on. The specific values of the attributes are the data to be analyzed. The overall goal is to find structure (information) about these data. This can be achieved by classifying the huge amount of data into relatively few classes of similar objects. This leads to a complexity reduction in the considered application which allows for improved decisions based on the gained information. Figure 9.1 shows the process of data analysis described so far which can be separated into feature analysis, classifier design, and classification.
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Zimmermann, HJ., Angstenberger, J., Weber, R. (1999). Intelligent Data Analysis and Fuzzy Control. In: Verbruggen, H.B., Zimmermann, HJ., Babuška, R. (eds) Fuzzy Algorithms for Control. International Series in Intelligent Technologies, vol 14. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-4405-6_9
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DOI: https://doi.org/10.1007/978-94-011-4405-6_9
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