Abstract
This chapter introduces the standard formulation for the data input to data mining algorithms that will be assumed throughout this book. It goes on to distinguish between different types of variable and to consider issues relating to the preparation of data prior to use, particularly the presence of missing data values and noise. The UCI Repository of datasets is introduced.
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Reference
Blake, C. L., & Merz, C. J. (1998). UCI repository of machine learning databases. Irvine: University of California, Department of Information and Computer Science. http://www.ics.uci.edu/~mlearn/MLRepository.html .
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Bramer, M. (2016). Data for Data Mining. In: Principles of Data Mining. Undergraduate Topics in Computer Science. Springer, London. https://doi.org/10.1007/978-1-4471-7307-6_2
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DOI: https://doi.org/10.1007/978-1-4471-7307-6_2
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