本文整理汇总了Python中sklearn.decomposition.IncrementalPCA.n_samples_seen_方法的典型用法代码示例。如果您正苦于以下问题：Python IncrementalPCA.n_samples_seen_方法的具体用法？Python IncrementalPCA.n_samples_seen_怎么用？Python IncrementalPCA.n_samples_seen_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.IncrementalPCA的用法示例。
在下文中一共展示了IncrementalPCA.n_samples_seen_方法的1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_incremental_pca_partial_fit_float_division
# 需要导入模块: from sklearn.decomposition import IncrementalPCA [as 别名]
# 或者: from sklearn.decomposition.IncrementalPCA import n_samples_seen_ [as 别名]
def test_incremental_pca_partial_fit_float_division():
# Test to ensure float division is used in all versions of Python
# (non-regression test for issue #9489)
rng = np.random.RandomState(0)
A = rng.randn(5, 3) + 2
B = rng.randn(7, 3) + 5
pca = IncrementalPCA(n_components=2)
pca.partial_fit(A)
# Set n_samples_seen_ to be a floating point number instead of an int
pca.n_samples_seen_ = float(pca.n_samples_seen_)
pca.partial_fit(B)
singular_vals_float_samples_seen = pca.singular_values_
pca2 = IncrementalPCA(n_components=2)
pca2.partial_fit(A)
pca2.partial_fit(B)
singular_vals_int_samples_seen = pca2.singular_values_
np.testing.assert_allclose(singular_vals_float_samples_seen,
singular_vals_int_samples_seen)