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Features/469 kmeans rework #470

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merged 12 commits into from
Feb 6, 2020
Merged

Features/469 kmeans rework #470

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9467402
Move heat/core/cluster to heat/cluster (Addresses Issue #467)
Cdebus Jan 30, 2020
f347cb8
Implementation of cdist
Cdebus Jan 30, 2020
f4ce203
run Hooks
Cdebus Jan 30, 2020
c2eaca9
Update setup.py
Cdebus Feb 3, 2020
fb0a911
Testing for spatial.distance cdist
Cdebus Feb 5, 2020
5348451
Move Regression from heat/core/ to heat/ directly
Cdebus Feb 5, 2020
e82381e
Bugfix for Lasso Test
Cdebus Feb 5, 2020
9d9ebba
Adjust demo to refactorization of regression
Cdebus Feb 5, 2020
748b68c
Merged master
Cdebus Feb 5, 2020
cde05a8
More testing for CodeCov
Cdebus Feb 5, 2020
25b68bf
Exception Throwing for dtypes other than float32 in spatial.distances…
Cdebus Feb 6, 2020
e6ad627
Added PR link to Changelog
Cdebus Feb 6, 2020
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Bugfix for Lasso Test
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@Cdebus
Cdebus committed Feb 5, 2020
commit e82381e5f6a95b0c4141316a978c9be7b72b3c85
6 changes: 3 additions & 3 deletions heat/regression/lasso/tests/test_lasso.py
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Original file line number Diff line number Diff line change
Expand Up @@ -38,7 +38,7 @@ def test_lasso(self):
X = X / ht.sqrt((ht.mean(X ** 2, axis=0)))
m, n = X.shape
# HeAT lasso instance
estimator = ht.core.regression.lasso.HeatLasso(max_iter=100, tol=None)
estimator = ht.regression.lasso.HeatLasso(max_iter=100, tol=None)
# check whether the results are correct
self.assertEqual(estimator.lam, 0.1)
self.assertTrue(estimator.theta is None)
Expand Down Expand Up @@ -82,7 +82,7 @@ def test_lasso(self):
X = X / torch.sqrt((torch.mean(X ** 2, 0)))
m, n = X.shape

estimator = ht.core.regression.lasso.PytorchLasso(max_iter=100, tol=None)
estimator = ht.regression.lasso.PytorchLasso(max_iter=100, tol=None)
# check whether the results are correct
self.assertEqual(estimator.lam, 0.1)
self.assertTrue(estimator.theta is None)
Expand Down Expand Up @@ -126,7 +126,7 @@ def test_lasso(self):
X = X / np.sqrt((np.mean(X ** 2, axis=0, keepdims=True)))
m, n = X.shape

estimator = ht.core.regression.lasso.NumpyLasso(max_iter=100, tol=None)
estimator = ht.regression.lasso.NumpyLasso(max_iter=100, tol=None)
# check whether the results are correct
self.assertEqual(estimator.lam, 0.1)
self.assertTrue(estimator.theta is None)
Expand Down