The anomaly detection task is very important in computer science. And there are a lot of anomalydetection methods. Different from some thresholding methods, some unsupervised methods couldmake us get more accurate and faster result, which is the object of the project. In this paper, Itried to use EWMA and some other methods in two datasets: Webank time consuming indicatorsdataset and AIOps Challenge dataset. The paper consists nine parts: background of the project,related work, description of algorithms, implementation details, experimental setup and data setsused, experimental results and discussion, future directions, reference and meeting notes.
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Subject: Computer Science and Mathematics - Computer Science
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