Hi, I am new to Apache Spark (any open source project). I want to contribute to it. I found that MLlib has no algorithm for outlier detection yet. By literature review I found the algorithm Attribute Value Frequency (AVF) is promising. Here is the link DOI: 10.1109/ICTAI.2007.125
By following the process I figured out that, I have to open a new feature request at JIRA (https://issues.apache.org/jira/browse/SPARK). Also, I have checked that no other issue is opened on "outlier detection". I want to know is it the right way to go? What project owners have in mind about outlier detection? Also is anybody working on parallel K nearest neighbour? Apart from opening up the feature request then pull request from git, How to provide the test cases? Suggestions and guidance are welcome. Thanks, Ashutosh -- View this message in context: http://apache-spark-developers-list.1001551.n3.nabble.com/MLlib-Contributing-Algorithm-for-Outlier-Detection-tp8880.html Sent from the Apache Spark Developers List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@spark.apache.org For additional commands, e-mail: dev-h...@spark.apache.org
