Abstract
This chapter introduces classification, one of the most common data mining tasks. Two classification algorithms are described in detail: the Naïve Bayes algorithm, which uses probability theory to find the most likely of the possible classifications, and Nearest Neighbour classification, which estimates the classification of an unseen instance using the classification of the instances ‘closest’ to it. These two methods generally assume that all the attributes are categorical and continuous, respectively.
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© 2016 Springer-Verlag London Ltd.
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Bramer, M. (2016). Introduction to Classification: Naïve Bayes and Nearest Neighbour. In: Principles of Data Mining. Undergraduate Topics in Computer Science. Springer, London. https://doi.org/10.1007/978-1-4471-7307-6_3
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DOI: https://doi.org/10.1007/978-1-4471-7307-6_3
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Publisher Name: Springer, London
Print ISBN: 978-1-4471-7306-9
Online ISBN: 978-1-4471-7307-6
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