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| author | Vasil Zlatanov <v@skozl.com> | 2019-02-04 19:02:43 +0000 |
|---|---|---|
| committer | Vasil Zlatanov <v@skozl.com> | 2019-02-04 19:02:43 +0000 |
| commit | d248ef0e0c9c9e7b924c3508f43e339687975627 (patch) | |
| tree | 59ebeaf1c190b78e536ecbeb2fe2c66b9be9f080 | |
| parent | 1f4c2737c59abee6f6291c1cffc2befdad386e1b (diff) | |
| download | e4-vision-d248ef0e0c9c9e7b924c3508f43e339687975627.tar.gz e4-vision-d248ef0e0c9c9e7b924c3508f43e339687975627.tar.bz2 e4-vision-d248ef0e0c9c9e7b924c3508f43e339687975627.zip | |
Remove hardcoded leaf limit
| -rwxr-xr-x | evaluate.py | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/evaluate.py b/evaluate.py index 9e3a613..92c4107 100755 --- a/evaluate.py +++ b/evaluate.py @@ -7,7 +7,7 @@ CLUSTER_CNT = 256 KMEANS = False if KMEANS: - N_ESTIMATORS = 10 + N_ESTIMATORS = 1000 else: N_ESTIMATORS = 1 @@ -29,7 +29,7 @@ if (KMEANS): print("Computing KMeans with", train_part.shape[0], "keywords") kmeans = KMeans(n_clusters=CLUSTER_CNT, n_init=N_ESTIMATORS, random_state=0).fit(train_part) else: - trees = RandomTreesEmbedding(max_leaf_nodes=256, n_estimators=N_ESTIMATORS, random_state=0).fit(train_part) + trees = RandomTreesEmbedding(max_leaf_nodes=CLUSTER_CNT, n_estimators=N_ESTIMATORS, random_state=0).fit(train_part) print("Generating histograms") |