本文整理汇总了Python中sklearn.metrics.base._average_binary_score方法的典型用法代码示例。如果您正苦于以下问题：Python base._average_binary_score方法的具体用法？Python base._average_binary_score怎么用？Python base._average_binary_score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.metrics.base的用法示例。
在下文中一共展示了base._average_binary_score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_averaging_multilabel_all_zeroes
# 需要导入模块: from sklearn.metrics import base [as 别名]
# 或者: from sklearn.metrics.base import _average_binary_score [as 别名]
def test_averaging_multilabel_all_zeroes():
y_true = np.zeros((20, 3))
y_pred = np.zeros((20, 3))
y_score = np.zeros((20, 3))
y_true_binarize = y_true
y_pred_binarize = y_pred
for name in METRICS_WITH_AVERAGING:
yield (_named_check(check_averaging, name), name, y_true,
y_true_binarize, y_pred, y_pred_binarize, y_score)
# Test _average_binary_score for weight.sum() == 0
binary_metric = (lambda y_true, y_score, average="macro":
_average_binary_score(
precision_score, y_true, y_score, average))
_check_averaging(binary_metric, y_true, y_pred, y_true_binarize,
y_pred_binarize, is_multilabel=True) 示例2: average_precision_score
# 需要导入模块: from sklearn.metrics import base [as 别名]
# 或者: from sklearn.metrics.base import _average_binary_score [as 别名]
def average_precision_score(y_true, y_score, average="macro",
sample_weight=None):
def _binary_average_precision(y_true, y_score, sample_weight=None):
precision, recall, thresholds = precision_recall_curve(
y_true, y_score, sample_weight=sample_weight)
return auc(recall, precision)
return _average_binary_score(_binary_average_precision, y_true, y_score,
average, sample_weight=sample_weight) 示例3: test_averaging_binary_multilabel_all_zeroes
# 需要导入模块: from sklearn.metrics import base [as 别名]
# 或者: from sklearn.metrics.base import _average_binary_score [as 别名]
def test_averaging_binary_multilabel_all_zeroes():
y_true = np.zeros((20, 3))
y_pred = np.zeros((20, 3))
y_true_binarize = y_true
y_pred_binarize = y_pred
# Test _average_binary_score for weight.sum() == 0
binary_metric = (lambda y_true, y_score, average="macro":
_average_binary_score(
precision_score, y_true, y_score, average))
_check_averaging(binary_metric, y_true, y_pred, y_true_binarize,
y_pred_binarize, is_multilabel=True)