本文整理汇总了Python中sklearn.decomposition.DictionaryLearning.set_params方法的典型用法代码示例。如果您正苦于以下问题：Python DictionaryLearning.set_params方法的具体用法？Python DictionaryLearning.set_params怎么用？Python DictionaryLearning.set_params使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类sklearn.decomposition.DictionaryLearning的用法示例。
在下文中一共展示了DictionaryLearning.set_params方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_dict_learning_nonzero_coefs
# 需要导入模块: from sklearn.decomposition import DictionaryLearning [as 别名]
# 或者: from sklearn.decomposition.DictionaryLearning import set_params [as 别名]
def test_dict_learning_nonzero_coefs():
n_components = 4
dico = DictionaryLearning(n_components, transform_algorithm='lars',
transform_n_nonzero_coefs=3, random_state=0)
code = dico.fit(X).transform(X[np.newaxis, 1])
assert_true(len(np.flatnonzero(code)) == 3)
dico.set_params(transform_algorithm='omp')
code = dico.transform(X[np.newaxis, 1])
assert_equal(len(np.flatnonzero(code)), 3)示例2: test_dict_learning_reconstruction
# 需要导入模块: from sklearn.decomposition import DictionaryLearning [as 别名]
# 或者: from sklearn.decomposition.DictionaryLearning import set_params [as 别名]
def test_dict_learning_reconstruction():
n_components = 12
dico = DictionaryLearning(n_components, transform_algorithm='omp',
transform_alpha=0.001, random_state=0)
code = dico.fit(X).transform(X)
assert_array_almost_equal(np.dot(code, dico.components_), X)
dico.set_params(transform_algorithm='lasso_lars')
code = dico.transform(X)
assert_array_almost_equal(np.dot(code, dico.components_), X, decimal=2)示例3: test_dict_learning_reconstruction_parallel
# 需要导入模块: from sklearn.decomposition import DictionaryLearning [as 别名]
# 或者: from sklearn.decomposition.DictionaryLearning import set_params [as 别名]
def test_dict_learning_reconstruction_parallel():
# regression test that parallel reconstruction works with n_jobs=-1
n_components = 12
dico = DictionaryLearning(n_components, transform_algorithm='omp',
transform_alpha=0.001, random_state=0, n_jobs=-1)
code = dico.fit(X).transform(X)
assert_array_almost_equal(np.dot(code, dico.components_), X)
dico.set_params(transform_algorithm='lasso_lars')
code = dico.transform(X)
assert_array_almost_equal(np.dot(code, dico.components_), X, decimal=2)