本文整理汇总了Python中mlxtend.evaluate.scoring函数的典型用法代码示例。如果您正苦于以下问题：Python scoring函数的具体用法？Python scoring怎么用？Python scoring使用的例子？那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。
在下文中一共展示了scoring函数的15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_metric_argument
def test_metric_argument():
"Test exception is raised when user provides invalid metric argument"
try:
scoring(y_target=[1], y_predicted=[1], metric='test')
assert False
except AttributeError:
assert True示例2: test_y_arguments
def test_y_arguments():
"Test exception is raised when user provides invalid vectors"
try:
scoring(y_target=[1, 2], y_predicted=[1])
assert False
except AttributeError:
assert True示例3: test_binary
def test_binary():
"Test exception is raised if label is not binary in f1"
try:
y_targ = [1, 1, 1, 0, 0, 2, 0, 3]
y_pred = [1, 0, 1, 0, 0, 2, 1, 3]
scoring(y_target=y_targ, y_predicted=y_pred, metric='f1')
assert False
except AttributeError:
assert True示例4: test_falsepositiverate
def test_falsepositiverate():
y_targ = [1, 1, 1, 0, 0, 1, 0, 1]
y_pred = [1, 0, 1, 0, 0, 0, 1, 1]
res = scoring(y_target=y_targ,
y_predicted=y_pred,
metric='false_positive_rate')
assert round(res, 3) == 0.333, res示例5: test_avg_perclass_error
def test_avg_perclass_error():
y_targ = np.array([0, 0, 0, 1, 1, 1, 1, 1, 2, 2])
y_pred = np.array([0, 1, 1, 0, 1, 1, 2, 2, 2, 2])
res = scoring(y_target=y_targ,
y_predicted=y_pred,
metric='per-class error')
assert round(res, 3) == 0.333, res示例6: test_avg_perclass_accuracy
def test_avg_perclass_accuracy():
y_targ = np.array([0, 0, 0, 1, 1, 1, 1, 1, 2, 2])
y_pred = np.array([0, 1, 1, 0, 1, 1, 2, 2, 2, 2])
res = scoring(y_target=y_targ,
y_predicted=y_pred,
metric='per-class accuracy')
assert round(res, 3) == 0.667, res示例7: test_matthews_corr_coef
def test_matthews_corr_coef():
y_targ = [1, 1, 1, 0, 0, 1, 0, 1]
y_pred = [1, 0, 1, 0, 0, 0, 1, 1]
res = scoring(y_target=y_targ,
y_predicted=y_pred,
metric='matthews_corr_coef')
assert round(res, 3) == 0.258, res示例8: test_sensitivity
def test_sensitivity():
y_targ = [1, 1, 1, 0, 0, 1, 0, 1]
y_pred = [1, 0, 1, 0, 0, 0, 1, 1]
res = scoring(y_target=y_targ, y_predicted=y_pred, metric='sensitivity')
assert round(res, 3) == 0.6, res示例9: test_specificity
def test_specificity():
y_targ = [1, 1, 1, 0, 0, 1, 0, 1]
y_pred = [1, 0, 1, 0, 0, 0, 1, 1]
res = scoring(y_target=y_targ, y_predicted=y_pred, metric='specificity')
assert round(res, 3) == 0.667, res示例10: test_recall
def test_recall():
y_targ = [1, 1, 1, 0, 0, 1, 0, 1]
y_pred = [1, 0, 1, 0, 0, 0, 1, 1]
res = scoring(y_target=y_targ, y_predicted=y_pred, metric='recall')
assert round(res, 3) == 0.6, res示例11: test_precision
def test_precision():
y_targ = [1, 1, 1, 0, 0, 1, 0, 1]
y_pred = [1, 0, 1, 0, 0, 0, 1, 1]
res = scoring(y_target=y_targ, y_predicted=y_pred, metric='precision')
assert round(res, 3) == 0.75, res示例12: test_error
def test_error():
"Test error metric"
y_targ = [1, 1, 1, 0, 0, 2, 0, 3]
y_pred = [1, 0, 1, 0, 0, 2, 1, 3]
res = scoring(y_target=y_targ, y_predicted=y_pred, metric='error')
assert res == 0.25示例13: test_accuracy
def test_accuracy():
"Test accuracy metric"
y_targ = [1, 1, 1, 0, 0, 2, 0, 3]
y_pred = [1, 0, 1, 0, 0, 2, 1, 3]
res = scoring(y_target=y_targ, y_predicted=y_pred, metric='accuracy')
assert res == 0.75示例14: test_f1
def test_f1():
y_targ = [1, 1, 1, 0, 0, 1, 0, 1]
y_pred = [1, 0, 1, 0, 0, 0, 1, 1]
res = scoring(y_target=y_targ, y_predicted=y_pred, metric='f1')
assert round(res, 3) == 0.667, res示例15: test_truepositiverate
def test_truepositiverate():
y_targ = [1, 1, 1, 0, 0, 1, 0, 1]
y_pred = [1, 0, 1, 0, 0, 0, 1, 1]
res = scoring(y_target=y_targ, y_predicted=y_pred, metric="true_positive_rate")
assert round(res, 3) == 0.6, res