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Posted to issues@spark.apache.org by "Fangzhou Yang (JIRA)" <ji...@apache.org> on 2017/12/22 03:12:02 UTC

[jira] [Created] (SPARK-22867) Add Isolation Forest algorithm to MLlib

Fangzhou Yang created SPARK-22867:
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             Summary: Add Isolation Forest algorithm to MLlib
                 Key: SPARK-22867
                 URL: https://issues.apache.org/jira/browse/SPARK-22867
             Project: Spark
          Issue Type: New Feature
          Components: MLlib
    Affects Versions: 2.2.1
            Reporter: Fangzhou Yang


Isolation Forest (iForest) is an effective model that focuses on anomaly isolation. 
iForest uses tree structure for modeling data, iTree isolates anomalies closer to the root of the tree as compared to normal points. 
A anomaly score is calculated by iForest model to measure the abnormality of the data instances. The lower, the more abnormal.

More details about iForest can be found in the following papers: 
<a href="https://dl.acm.org/citation.cfm?id=1511387">Isolation Forest</a> [1] 
and <a href="https://dl.acm.org/citation.cfm?id=2133363">Isolation-Based Anomaly Detection</a> [2].



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