Abstract
As we stated in the introductory chapter, data mining originates from many scientific areas, one of them being Statistics. Having in mind that data mining is an analytic process designed to explore large amounts of data in search of consistent and valuable hidden knowledge, the first step made in this fabulous research field consists in an initial data exploration. For building various models and choosing the best one, based on their predictive performance, it is necessary to perform a preliminary exploration of the data to better understand their characteristics. This stage usually starts with data preparation. Then, depending on the nature of the problem to be solved, it can involve anything from simple descriptive statistics to regression models, time series, multivariate exploratory techniques, etc. The aim of this chapter is therefore to provide an overview of the main topics concerning this data analysis.
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© 2011 Springer-Verlag Berlin Heidelberg
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Gorunescu, F. (2011). Exploratory Data Analysis. In: Data Mining. Intelligent Systems Reference Library, vol 12. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19721-5_3
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DOI: https://doi.org/10.1007/978-3-642-19721-5_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19720-8
Online ISBN: 978-3-642-19721-5
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