本文整理汇总了Python中lightning.impl.primal_cd.CDClassifier.n_nonzero方法的典型用法代码示例。如果您正苦于以下问题：Python CDClassifier.n_nonzero方法的具体用法？Python CDClassifier.n_nonzero怎么用？Python CDClassifier.n_nonzero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lightning.impl.primal_cd.CDClassifier的用法示例。
在下文中一共展示了CDClassifier.n_nonzero方法的7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_empty_model
# 需要导入模块: from lightning.impl.primal_cd import CDClassifier [as 别名]
# 或者: from lightning.impl.primal_cd.CDClassifier import n_nonzero [as 别名]
def test_empty_model():
clf = CDClassifier(C=1e-5, penalty="l1")
clf.fit(bin_dense, bin_target)
assert_equal(clf.n_nonzero(), 0)
acc = clf.score(bin_dense, bin_target)
assert_equal(acc, 0.5)
clf = CDClassifier(C=1e-5, penalty="l1", debiasing=True)
clf.fit(bin_dense, bin_target)
assert_equal(clf.n_nonzero(), 0)
acc = clf.score(bin_dense, bin_target)
assert_equal(acc, 0.5)示例2: test_warm_start_l1r
# 需要导入模块: from lightning.impl.primal_cd import CDClassifier [as 别名]
# 或者: from lightning.impl.primal_cd.CDClassifier import n_nonzero [as 别名]
def test_warm_start_l1r():
clf = CDClassifier(warm_start=True, random_state=0, penalty="l1")
clf.C = 0.1
clf.fit(bin_dense, bin_target)
n_nz = clf.n_nonzero()
clf.C = 0.2
clf.fit(bin_dense, bin_target)
n_nz2 = clf.n_nonzero()
assert_true(n_nz < n_nz2)示例3: test_debiasing_warm_start
# 需要导入模块: from lightning.impl.primal_cd import CDClassifier [as 别名]
# 或者: from lightning.impl.primal_cd.CDClassifier import n_nonzero [as 别名]
def test_debiasing_warm_start():
clf = CDClassifier(penalty="l1", max_iter=10,
warm_start=True, random_state=0)
clf.C = 0.5
clf.fit(bin_dense, bin_target)
assert_equal(clf.n_nonzero(), 74)
assert_almost_equal(clf.score(bin_dense, bin_target), 1.0)
clf.C = 1.0
clf.fit(bin_dense, bin_target)
# FIXME: not the same sparsity as without warm start...
assert_equal(clf.n_nonzero(), 77)
assert_almost_equal(clf.score(bin_dense, bin_target), 1.0)示例4: test_debiasing_l1
# 需要导入模块: from lightning.impl.primal_cd import CDClassifier [as 别名]
# 或者: from lightning.impl.primal_cd.CDClassifier import n_nonzero [as 别名]
def test_debiasing_l1():
for warm_debiasing in (True, False):
clf = CDClassifier(penalty="l1", debiasing=True,
warm_debiasing=warm_debiasing,
C=0.05, Cd=1.0, max_iter=10, random_state=0)
clf.fit(bin_dense, bin_target)
assert_equal(clf.n_nonzero(), 22)
assert_almost_equal(clf.score(bin_dense, bin_target), 0.955, 3)示例5: test_fit_linear_binary_l1r
# 需要导入模块: from lightning.impl.primal_cd import CDClassifier [as 别名]
# 或者: from lightning.impl.primal_cd.CDClassifier import n_nonzero [as 别名]
def test_fit_linear_binary_l1r():
clf = CDClassifier(C=1.0, random_state=0, penalty="l1")
clf.fit(bin_dense, bin_target)
acc = clf.score(bin_dense, bin_target)
assert_almost_equal(acc, 1.0)
n_nz = clf.n_nonzero()
perc = clf.n_nonzero(percentage=True)
assert_equal(perc, float(n_nz) / bin_dense.shape[1])
clf = CDClassifier(C=0.1, random_state=0, penalty="l1")
clf.fit(bin_dense, bin_target)
acc = clf.score(bin_dense, bin_target)
assert_almost_equal(acc, 0.97)
n_nz2 = clf.n_nonzero()
perc2 = clf.n_nonzero(percentage=True)
assert_equal(perc2, float(n_nz2) / bin_dense.shape[1])
assert_true(n_nz > n_nz2)示例6: test_debiasing_l1l2
# 需要导入模块: from lightning.impl.primal_cd import CDClassifier [as 别名]
# 或者: from lightning.impl.primal_cd.CDClassifier import n_nonzero [as 别名]
def test_debiasing_l1l2():
for warm_debiasing in (True, False):
clf = CDClassifier(penalty="l1/l2", loss="squared_hinge",
multiclass=False,
debiasing=True,
warm_debiasing=warm_debiasing,
max_iter=20, C=0.01, random_state=0)
clf.fit(mult_csc, mult_target)
assert_greater(clf.score(mult_csc, mult_target), 0.75)
assert_equal(clf.n_nonzero(percentage=True), 0.08)示例7: test_fit_squared_loss_l1
# 需要导入模块: from lightning.impl.primal_cd import CDClassifier [as 别名]
# 或者: from lightning.impl.primal_cd.CDClassifier import n_nonzero [as 别名]
def test_fit_squared_loss_l1():
clf = CDClassifier(C=0.5, random_state=0, penalty="l1",
loss="squared", max_iter=100, shrinking=False)
clf.fit(bin_dense, bin_target)
assert_almost_equal(clf.score(bin_dense, bin_target), 0.985, 3)
y = bin_target.copy()
y[y == 0] = -1
assert_array_almost_equal(np.dot(bin_dense, clf.coef_.ravel()) - y,
clf.errors_.ravel())
n_nz = clf.n_nonzero()
assert_equal(n_nz, 89)