Mixture or logistic regression estimation for discrimination

Terence J. O'Neill

Statistics & Probability Letters, 1994, vol. 20, issue 2, 139-142

Abstract: When a training sample for a classification rule includes unclassified observations, the estimation can be done by maximum likelihood using both the classified and unclassified data (GM) or (assuming an exponential family) by logistic regression (L) on the classified data only. This paper shows that the choice depends on the separation and shape of the family.

Keywords: Logistic; regression; Mixtures; Unclassified; observations (search for similar items in EconPapers)
Date: 1994
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