Ridge Discriminant Analysis.
WYOMING UNIV LARAMIE STATISTICS LAB
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Discriminant analysis is one of the more commonly applied multivariate techniques. The performance of the sample linear discriminant function usually employed depends on the quality of the estimates of the parameters involved, but especially on the estimate of the covariance matrix of the population. It is demonstrated that an improved classification process is possible with techniques similar to those of ridge regression. A Monte Carlo study is undertaken to examine the extent of the improvement possible and to determine a reasonable criterion for selecting the ridge constant. Application of the method is discussed.
- Statistics and Probability