Abstract
Suppose we are given a learning set \(\mathcal{L}\) of multivariate observations (i.e., input values \(\mathfrak{R}^r\)), and suppose each observation is known to have come from one of K predefined classes having similar characteristics. These classes may be identified, for example, as species of plants, levels of credit worthiness of customers, presence or absence of a specific medical condition, different types of tumors, views on Internet censorship, or whether an e-mail message is spam or non-spam.
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© 2013 Springer Science+Business Media New York
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Izenman, A.J. (2013). Linear Discriminant Analysis. In: Modern Multivariate Statistical Techniques. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-78189-1_8
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DOI: https://doi.org/10.1007/978-0-387-78189-1_8
Publisher Name: Springer, New York, NY
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