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diff --git a/knn/README b/knn/README new file mode 100644 index 0000000..c87f31c --- /dev/null +++ b/knn/README @@ -0,0 +1,20 @@ +k-NN object for PD + +Introduction + +The k Nearest Neighbor algorithm is a simple and robust classification +algorithm. It compares an unknown feature vector to a database by +calculating distance and assigns the classification of the k closest +database entries to the unknown vector. This implementation for PD +takes inputs of PD lists for both learning and classification. +Currently the length of the feature vectors and maximum number of +classes is fixed at compile time. + +Feature Weighting + +This implementation also includes feature weighting to allow control +over the relative importance of each feature. This has been shown to +provide significant improvements to the performance of the k-NN +algorithm. + +Karl MacMillan <karlmac@peabody.jhu.edu>
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