For each feature vector v in the test set, we compute the Euclidean distance to each of the matching vectors in the extended training set, where matching vectors share at least one pattern feature with v. Let t i , i = 1..k be the k vectors with lowest Euclidean distance to v 6 .
then v is classified with a label l as follows: j Count(label(t j )) the score is a weighted average of the k closest training set vectors.