From 37434f5baf632e839dc14b3c7d8745287cb9368a Mon Sep 17 00:00:00 2001 From: Douglas Rumbaugh Date: Tue, 25 Jul 2023 11:17:36 -0400 Subject: Benchmarks: mtree and vptree benchmark updates Note: cosine similarity doesn't seem to work for VPTree--I don't think that it is actually a metric, upon further research. At the very least I can't find anyone claiming it is, and I've found several people claiming it isn't. On testing with the Word2Vec data, Euclidean distance works insofar as the M-Tree and VPTree return the same KNN results for test queries, whereas Cosine Similarity does not work. --- benchmarks/vptree_knn_bench.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'benchmarks/vptree_knn_bench.cpp') diff --git a/benchmarks/vptree_knn_bench.cpp b/benchmarks/vptree_knn_bench.cpp index a5c45f4..0021c4a 100644 --- a/benchmarks/vptree_knn_bench.cpp +++ b/benchmarks/vptree_knn_bench.cpp @@ -19,7 +19,7 @@ int main(int argc, char **argv) double insert_batch = 0.1; init_bench_env(record_count, true); - auto queries = read_knn_queries>(qfilename, 50); + auto queries = read_knn_queries>(qfilename, 10); auto de_vp_knn = ExtendedVPTree_KNN(buffer_cap, scale_factor, max_delete_prop); -- cgit v1.2.3