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Posted to commits@systemml.apache.org by gw...@apache.org on 2017/04/16 17:56:54 UTC
incubator-systemml git commit: [SYSTEMML-1529] Improve accuracy score
in test_svm of test_mllearn_numpy.py
Repository: incubator-systemml
Updated Branches:
refs/heads/master 0d625a05e -> 499428072
[SYSTEMML-1529] Improve accuracy score in test_svm of test_mllearn_numpy.py
Adjusted tolerance parameter in test_svm to help prevent occasional
failure due to accuracy not meeting test criteria of greater than 95%.
Closes #460.
Project: http://git-wip-us.apache.org/repos/asf/incubator-systemml/repo
Commit: http://git-wip-us.apache.org/repos/asf/incubator-systemml/commit/49942807
Tree: http://git-wip-us.apache.org/repos/asf/incubator-systemml/tree/49942807
Diff: http://git-wip-us.apache.org/repos/asf/incubator-systemml/diff/49942807
Branch: refs/heads/master
Commit: 499428072b53fbc63547d190a85e551c11c4d474
Parents: 0d625a0
Author: Glenn Weidner <gw...@us.ibm.com>
Authored: Sun Apr 16 10:53:49 2017 -0700
Committer: Glenn Weidner <gw...@us.ibm.com>
Committed: Sun Apr 16 10:53:49 2017 -0700
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src/main/python/tests/test_mllearn_numpy.py | 6 ++++--
1 file changed, 4 insertions(+), 2 deletions(-)
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http://git-wip-us.apache.org/repos/asf/incubator-systemml/blob/49942807/src/main/python/tests/test_mllearn_numpy.py
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diff --git a/src/main/python/tests/test_mllearn_numpy.py b/src/main/python/tests/test_mllearn_numpy.py
index faa4d32..2a1bc3c 100644
--- a/src/main/python/tests/test_mllearn_numpy.py
+++ b/src/main/python/tests/test_mllearn_numpy.py
@@ -149,12 +149,14 @@ class TestMLLearn(unittest.TestCase):
y_train = y_digits[:int(.9 * n_samples)]
X_test = X_digits[int(.9 * n_samples):]
y_test = y_digits[int(.9 * n_samples):]
- svm = SVM(sparkSession, is_multi_class=True)
+ svm = SVM(sparkSession, is_multi_class=True, tol=0.0001)
mllearn_predicted = svm.fit(X_train, y_train).predict(X_test)
from sklearn import linear_model, svm
clf = svm.LinearSVC()
sklearn_predicted = clf.fit(X_train, y_train).predict(X_test)
- self.failUnless(accuracy_score(sklearn_predicted, mllearn_predicted) > 0.95 )
+ accuracy = accuracy_score(sklearn_predicted, mllearn_predicted)
+ evaluation = 'test_svm accuracy_score(sklearn_predicted, mllearn_predicted) was {}'.format(accuracy)
+ self.failUnless(accuracy > 0.95, evaluation)
def test_naive_bayes(self):
digits = datasets.load_digits()