-
Notifications
You must be signed in to change notification settings - Fork 16
New issue
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
关于FDG及failure units的若干疑问 #5
Comments
|
另外关于数据集还有几个问题: |
1. norm指的是归一化之后的指标数据
2. a1+a2=A数据集
3. 归一化方法主要用的是sklearn里面的robust scaler,另外有几个指标是特殊处理的。比如响应时间这种先取了对数
Zeyan LI 李则言
E-Mail: ***@***.***
Ph.D. student
Department of Computer Science
Tsinghua University
Beijing, China
在 2022年9月17日,21:22,adverbial39 ***@***.***> 写道:
另外关于数据集还有几个问题:
a1和a2中的metric和metric_norm是什么关系?a2的指标包含a1的,两个集之间有什么关系?
数据集中的数据是原始数据还是归一化后的数据,如果是归一化后的,请问使用了什么归一化方法?
—
Reply to this email directly, view it on GitHub<#5 (comment)>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AC7KLI4F43BOUE5MQW7QOWTV6XA2VANCNFSM6AAAAAAQM7GUNM>.
You are receiving this because you commented.Message ID: ***@***.***>
|
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
the experienced engineers of an online service system can define the candidate failure units by summarizing the indicative metric groups on different component classes.
可否理解为每个failure units的指标群是人工选择的?您在论文中提到“ For generalizability, the feature aggregator should be structure-independent. Thus, graph convolutional network (GCN) [29] is unsuitable.”能否详细解释一下为什么要考虑structure-independent
您在论文中有提到组件、部署关系会经常改变,这意味着FDG需要经常更新,这部分更新使利用专家经验完成吗?
无向图表达相互影响,而非单方面影响(依赖),为什么能反应依赖关系呢?
期待您的解答(╹▽╹)
The text was updated successfully, but these errors were encountered: