Computerized Pattern Recognition Applications to Chemical Analysis. Development of Interactive Feature Selection Methods for the K-Nearest Neighbor Technique.
Technical rept. no. 1, 1 Apr 73-21 Feb 74,
PURDUE UNIV LAFAYETTE IND DEPT OF CHEMISTRY
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A systematic approach has been developed for feature selection in the application of the K-nearest neighbor KNN computerized pattern recognition method. The approach uses an operator-interactive computer system. A large number of potentially-useful features for classification of patterns can be screened for the most relevant members by a combination of recommended procedures. These include a one-dimensional KNN classification of all patterns using each feature individually b inspection of histogram displays of classification records for each feature and c establishment of consensus classifications from combined one-dimensional results. A computerized trial-and-error procedure can then be implemented to find the best combination of a minimum number of features for accurate classification using the multi-dimensional KNN method. Modified author abstract
- Industrial Chemistry and Chemical Processing