Comparing the three algorithms we see that overall, kNN and the category-based method exhibit comparable performance (with the exception of measuring similarity by L1 distance, when the category-based method outperforms kNN by a margin of about 5 points; statistical significance p<0.001).
their performance is different in different frequency ranges: for lower frequencies kNN is more accurate (e.g., for L1 distance, p<0.001).