We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
感觉x-deeplearning 中auc 计算batch auc,把其中只包含negative的batch 算作invalid 抛弃,这个做法跟tensorflow里面做法不一样。会比较大的影响auc的计算,因为一个batch中没有positive 也会影响全局的FP,auc应该算全局的。 具体请看: alibaba/x-deeplearning#355
The text was updated successfully, but these errors were encountered:
你说的这个有一定的道理,因为esmm计算从view->conversion 因为非常稀疏,可能会有一些batch里面没有正常本, 但是实际操作过程中,应该尽量避免这种情况,如果很多batch里面都没有正样本,这其实是不利于模型的学习的。
Sorry, something went wrong.
阿里的数据集大概有30%多没有正例(去5000batch_size)。
No branches or pull requests
感觉x-deeplearning 中auc 计算batch auc,把其中只包含negative的batch 算作invalid 抛弃,这个做法跟tensorflow里面做法不一样。会比较大的影响auc的计算,因为一个batch中没有positive 也会影响全局的FP,auc应该算全局的。
具体请看: alibaba/x-deeplearning#355
The text was updated successfully, but these errors were encountered: