A note on learning for Gaussian properties
Daniel G. Keehn · IEEE Transactions on Information Theory · 1965
By employing a Bayesian approach to the analysis of learning the probability distribution of property vectors, an estimation likelihood computation scheme for the general Gaussian distribution (quadratic adaptive decision surface) is shown optimum. Some results relating the number of learning samples to Type I misclassification errors are included.