什么是多标签二分类？
What is the multi-label binary classification?
阅读 PyTorch 文档BCEWithLogitsLoss:
where c is the class number (c > 1 for multi-label binary classification, c = 1 for single-label binary classification), nn is the number of the sample in the batch and p_cp
c is the weight of the positive answer for the class cc .
什么是多标签二元分类？二进制假设只有两个标签 AFIK
二进制class化的多标签意味着对于单个示例，classes 都可以为真class。
例如，对于狗猫 classifier，对于同时包含狗和猫的图像，它会同时预测狗和猫。
In the multi-label problem there is no constraint on how many of the classes the instance can be assigned to. Wiki
阅读 PyTorch 文档BCEWithLogitsLoss:
where c is the class number (c > 1 for multi-label binary classification, c = 1 for single-label binary classification), nn is the number of the sample in the batch and p_cp c is the weight of the positive answer for the class cc .
什么是多标签二元分类？二进制假设只有两个标签 AFIK
二进制class化的多标签意味着对于单个示例，classes 都可以为真class。
例如，对于狗猫 classifier，对于同时包含狗和猫的图像，它会同时预测狗和猫。
In the multi-label problem there is no constraint on how many of the classes the instance can be assigned to. Wiki