Thank you 1zmm and PGStats. PGStats, I appreciate the suggestion to use of DT instead, but in this case is more of a methodological issue trying to solve this conundrum of scoring new cases after k-neighbors discrimiant. 1zmm, I built a small dataset and ran some tests following your advice. I cannot match my results with those I get in SAS scoring. I have been researching more on the topic (see link in previous post) and there is one critical issue I must solve: How to estimate group-specific densities for each new case. Quoting SAS, "Nonparametric discriminant methods are based on nonparametric estimates of group-specific probability densities". After densities are estimated "either Mahalanobis or Euclidean distance can be used to determine proximity. When the k-nearest-neighbor method is used, the Mahalanobis distances are based on the pooled covaraince matrix". More specifically, from SAS manual referenced above When scoring new cases in SAS with the TESTDATA= option, I can see the group-specific calculated densities for each case. I have been unable to match those numbers "manually". This is going out of scope for me. I need to find a way to do this efficiently with the output provided by SAS in the analysis (i.e., pooled covariance matrix, square distances, group means, etc.). I will be asking SAS support and will post any successful answer I get (if any). I very much appreciate all your comments. Thank you
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