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Posted to issues@spark.apache.org by "Ashutosh Trivedi (JIRA)" <ji...@apache.org> on 2014/10/21 21:31:34 UTC

[jira] [Created] (SPARK-4038) Outlier Detection Algorithm for MLlib

Ashutosh Trivedi created SPARK-4038:
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             Summary: Outlier Detection Algorithm for MLlib
                 Key: SPARK-4038
                 URL: https://issues.apache.org/jira/browse/SPARK-4038
             Project: Spark
          Issue Type: New Feature
          Components: MLlib
    Affects Versions: 1.2.0
            Reporter: Ashutosh Trivedi


The aim of this JIRA is to discuss about which parallel outlier detection algorithms can be included in MLlib. 
The one which I am familiar with is Attribute Value Frequency (AVF). It scales linearly with the number of data points and attributes, and relies on a single data scan. It is not distance based and well suited for categorical data. In original paper  a Parallel version is also given, which is not complected to implement. 
Here is the Link for the paper
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4410382





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