From 56ca0f1977bcb1dcd08649bbb817c4a142e703fe Mon Sep 17 00:00:00 2001
From: dlagul <dailiang@iie.ac.cn>
Date: Sun, 18 Oct 2020 21:22:48 +0800
Subject: [PATCH] Update README.md

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 README.md | 72 -------------------------------------------------------
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@@ -8,75 +8,3 @@ These labelled abnormal sequences are confirmed by human operators. So they can
 The KPIs in the datasets include the out-bound traffic and in-bound traffic of CDN servers, cache hit ratio, average bitrate, and so on. <br>
 For privacy reasons, these KPIs are anonymized and normalized. <br>
 
-
-## Dataset Information
-
-### Dataset1
-#### Basic Statistics
-
-Statistics | dataset1
---- | ---
-Number of KPIs | 24
-Durations (day) | 78
-Granularity (min) | 5
-Number of points | 22,356
-Number of anomaly sequences | 7
-Anomaly ratio (%) | 1.6
-Train period | 1 ∼ 10,656
-Test period | 10,657 ∼ 22,356
-
-#### Data format
-There are 24 CSV files and each file corresponds to a KPI. <br>
-The CSV has the following format: <br>
-* First column is the timestamp <br>
-* Second column is the value <br>
-* Third column is the label. 0 for normal and 1 for abnormal <br>
-
-Timestamp | Value | Label
---- | --- | ---
-20181001000500 | 0.46444977152338346 | 0
-20181001001000 | 0.4423121844530866 | 0
-20181001001500 | 0.4186436700242946 | 0
-20181001002000 | 0.39892597116922146 | 1
-20181001002500 | 0.37977501905111494 | 1
-20181001003000 | 0.36615750635812155 | 1
-
-### Dataset2
-
-#### Basic Statistics
-
-Statistics | dataset2
---- | ---
-Number of KPIs | 16
-Durations (day) | 64
-Granularity (min) | 1
-Number of points | 91,507
-Number of anomaly sequences | 5
-Anomaly ratio (%) | 0.32
-Train period | 1 ∼ 51,336
-Test period | 51,337 ∼ 91,507
-
-#### Data format
-There are 2 CSV files in the folder named "dataset2". <br>
-The file named "dataset2.csv" is the full data, and "dataset2_sample.csv" is the sample which contains 1000 records. <br>
-The CSV has the following format: <br>
-* First column is the timestamp <br>
-* 2nd~17th columns are the KPI values which correspond to 16 KPIs <br>
-* The last column is the label. 0 for normal and 1 for abnormal <br>
-
-Timestamp | Kpi1 | ... | Kpi16 | Label
---- | --- | --- | --- | ---
-20190903000200 | 0.46444977152338346 | ... | -0.588230235 | 0 |
-20190903000300 | 0.4423121844530866 | ... | -0.595955299 | 0 |
-20190903000400 | 0.4186436700242946 | ... | -0.600299795 | 0 |
-20190903000500 | 0.39892597116922146 | ... | -0.604815951 | 1 |
-20190903000600 | 0.37977501905111494 | ... | -0.610974025 | 1 |
-20190903000700 | 0.36615750635812155 | ... | -0.616264816 | 1 |
-
-### Public Dataset 
-The public dataset (SMD) used in our evaluation experiments as well as its detailed description can be found in web sites:
-https://github.com/NetManAIOps/OmniAnomaly
-
-For simplicity, we select 2 of 28 machine data namely "machine-1-2.txt" and "machine-1-3.txt" to conduct evaluation experiments.
-
-**Note that all KPIs are normalized and we omitted the real name of each KPI for confidentiality, but this does not affect the accuracy of the evaluation experiments.**
-- 
GitLab