[GitHub] [incubator-pinot] xiaohui-sun commented on a change in pull request #4466: [TE] Adding Mean Variance Rule Detector

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xiaohui-sun commented on a change in pull request #4466: [TE] Adding Mean Variance Rule Detector
URL: https://github.com/apache/incubator-pinot/pull/4466#discussion_r307106380
 
 

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 File path: thirdeye/thirdeye-pinot/src/main/java/org/apache/pinot/thirdeye/detection/spec/WoWStdRuleDetectorSpec.java
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 @@ -0,0 +1,60 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.pinot.thirdeye.detection.spec;
+
+import org.apache.pinot.thirdeye.dataframe.util.MetricSlice;
+import org.apache.pinot.thirdeye.detection.Pattern;
+
+
+public class WoWStdRuleDetectorSpec extends AbstractSpec {
+  private String monitoringGranularity = MetricSlice.NATIVE_GRANULARITY.toAggregationGranularityString(); // use native granularity by default
+  private int lookback = 52;
+  private double sensitivity = 1.5;
 
 Review comment:
   I think you can keep sigma. However the motivation of introducing 0-10 scale is to give a universal parameter setting across all anomaly detection functions. There are several benefits:
   1. Easy to understand. Users don't need to understand the methodology behind it. It could be p-value or sigma or others.
   2. Easy to switch between rules w/o changing parameters. E.g, user can set a sensitivity of 5 to expect a moderate sensitivity for all rules.
   I strongly encourage you to generate a mapping between sensitivity and sigma and expose sensitivity to user. If you want to expose sigma for users to fine control the model (like p-value) it is fine.

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