Abstract
This book deals with models and algorithms for the analysis of data sets, for example industrial process data, business data, text and structured data, image data, and biomedical data. We define the terms data analytics, data mining, knowledge discovery, and the KDD and CRISP-DM processes. Typical data analysis projects can be divided into several phases: preparation, preprocessing, analysis, and postprocessing. The chapters of this book are structured according to the main methods of data preprocessing and data analysis: data and relations, data preprocessing, visualization, correlation, regression, forecasting, classification, and clustering.
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Runkler, T.A. (2020). Introduction. In: Data Analytics. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-29779-4_1
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DOI: https://doi.org/10.1007/978-3-658-29779-4_1
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