From 123d70d9a91e15f6076ada072305ad2aaa0bd916 Mon Sep 17 00:00:00 2001
From: Gael Varoquaux <gael.varoquaux@normalesup.org>
Date: Sun, 6 May 2012 11:01:10 +0200
Subject: [PATCH] BUG test_oneclass_decision_function: fix RNG
Never oh never use an unprotected random number generator
Fixes #765
---
sklearn/svm/tests/test_svm.py | 7 ++++---
1 file changed, 4 insertions(+), 3 deletions(-)
diff --git a/sklearn/svm/tests/test_svm.py b/sklearn/svm/tests/test_svm.py
index 832fe12ce6..f66e80505b 100644
--- a/sklearn/svm/tests/test_svm.py
+++ b/sklearn/svm/tests/test_svm.py
@@ -21,7 +21,8 @@ true_result = [1, 2, 2]
# also load the iris dataset
iris = datasets.load_iris()
-perm = np.random.permutation(iris.target.size)
+rng = check_random_state(42)
+perm = rng.permutation(iris.target.size)
iris.data = iris.data[perm]
iris.target = iris.target[perm]
@@ -187,7 +188,7 @@ def test_oneclass_decision_function():
Test OneClassSVM decision function
"""
clf = svm.OneClassSVM()
- rnd = check_random_state(0)
+ rnd = check_random_state(2)
# Generate train data
X = 0.3 * rnd.randn(100, 2)
@@ -197,7 +198,7 @@ def test_oneclass_decision_function():
X = 0.3 * rnd.randn(20, 2)
X_test = np.r_[X + 2, X - 2]
# Generate some abnormal novel observations
- X_outliers = np.random.uniform(low=-4, high=4, size=(20, 2))
+ X_outliers = rnd.uniform(low=-4, high=4, size=(20, 2))
# fit the model
clf = svm.OneClassSVM(nu=0.1, kernel="rbf", gamma=0.1)
--
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