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[FIX] KNN: Fix crash when Mahanalobis metric is used #1475

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merged 2 commits into from
Jul 28, 2016

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VesnaT
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@VesnaT VesnaT commented Jul 21, 2016

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codecov-io commented Jul 21, 2016

Current coverage is 88.19% (diff: 100%)

Merging #1475 into master will increase coverage by <.01%

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@@ -11,5 +11,7 @@ class KNNLearner(SklLearner):
def __init__(self, n_neighbors=5, metric="euclidean", weights="uniform",
algorithm='auto',
preprocessors=None):
if metric == "mahalanobis":
algorithm = "brute"
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Please add a comment explaining why this is necessary. For the record, this works for me:

>>> from sklearn.neighbors import KNeighborsClassifier
>>> nn = KNeighborsClassifier(metric='mahalanobis', algorithm='auto')
>>> X = np.random.random((10, 2))
>>> y = (np.random.random(10) > .5).astype(int)
>>> nn.fit(X, y)
>>> nn.predict(X)
array([1, 1, 1, 1, 0, 0, 0, 0, 0, 0])

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For me as well. But i.e. X = np.random.random((12, 2)) doesn't.

@VesnaT VesnaT changed the title [FIX] KNN: Fix crash when Mahanalobis metric is used [WIP][FIX] KNN: Fix crash when Mahanalobis metric is used Jul 25, 2016
@VesnaT VesnaT changed the title [WIP][FIX] KNN: Fix crash when Mahanalobis metric is used [FIX] KNN: Fix crash when Mahanalobis metric is used Jul 25, 2016


class TestKNNLearner(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.iris = Table('iris')
cls.learn = KNNLearner()
cls.learn = KNNLearner
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I would skip assigning classes in to cls.learn and cls.learn_reg and just use their names in tests.

self.learn() is not much shorter than KNNLearner() (in fact it has the same number of characters)

VesnaT added 2 commits July 28, 2016 13:21
KNN learners (cls and reg) need additional parameter (metric_params) when Mahalanobis distance metric is used.
Since both learners have the same parameters, new base class was created.
@astaric astaric merged commit d46b8e1 into biolab:master Jul 28, 2016
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4 participants