Publication: The kurtosis coeficient and the linear discriminant function
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1999-10
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Abstract
In this note we analyze the relationship between the direction obtained from the
minimization of the kurtosis coefficient of the projections of a mixture of multivariate
normal distributions and the linear discriminant function. We show that both
directions are closely related, and in particular that given two vector random variables having symmetric distributions with unknown means and the same covariance matrix,the direction which minimizes the kurtosis coefficient of the projection is the linear discriminant function. This result provides a way to compute the discriminant function between two normal populations in the case in which the means and the common covariance matrix are unknown.
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Classification, kurtosis coefficient