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Data Mining pp 57-157 | Cite as

Exploratory Data Analysis

  • Florin Gorunescu
Chapter
  • 5.7k Downloads
Part of the Intelligent Systems Reference Library book series (ISRL, volume 12)

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.

Keywords

Anomaly Detection Functional Residual Capacity Total Lung Capacity Statistical Series Exploratory Data Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Florin Gorunescu

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