8000 [WIP] Draft: Precompute feature for PairwiseDistancesReductions by kyrajeep · Pull Request #29391 · scikit-learn/scikit-learn · GitHub
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[WIP] Draft: Precompute feature for PairwiseDistancesReductions #29391

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[WIP] Draft: Precompute feature for PairwiseDistancesReductions #29391

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831da32
Draft to optimize computation for the distance between two points
kyrajeep Jun 20, 2024
f1e801c
Add the option to bypass test for precomputed
kyrajeep Jul 2, 2024
a912954
Delete unrelated
kyrajeep Jul 2, 2024
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7 changes: 6 additions & 1 deletion sklearn/neighbors/tests/test_ball_tree.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,6 +20,7 @@
"manhattan": {},
"minkowski": dict(p=3),
"chebyshev": {},
"precomputed": {},
}

DISCRETE_METRICS = ["hamming", "canberra", "braycurtis"]
Expand All @@ -41,6 +42,9 @@

def brute_force_neighbors(X, Y, k, metric, **kwargs):
from sklearn.metrics import DistanceMetric

if metric == "precomputed":
return Y, np.argsort(Y, axis=1)[:, :k]

X, Y = check_array(X), check_array(Y)
D = DistanceMetric.get_metric(metric, **kwargs).pairwise(Y, X)
Expand Down Expand Up @@ -73,7 +77,8 @@ def test_ball_tree_query_metrics(metric, array_type, BallTreeImplementation):
dist1, ind1 = bt.query(Y, k)
dist2, ind2 = brute_force_neighbors(X, Y, k, metric)
assert_array_almost_equal(dist1, dist2)




@pytest.mark.parametrize(
"BallTreeImplementation, decimal_tol", zip(BALL_TREE_CLASSES, [6, 5])
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