[ https://issues.apache.org/jira/browse/FLINK-1933?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Till Rohrmann closed FLINK-1933. -------------------------------- Resolution: Fixed Added via ddb2b34704a410491d428dec2ade0cb20a58ed80 > Add distance measure interface and basic implementation to machine learning > library > ----------------------------------------------------------------------------------- > > Key: FLINK-1933 > URL: https://issues.apache.org/jira/browse/FLINK-1933 > Project: Flink > Issue Type: New Feature > Components: Machine Learning Library > Reporter: Chiwan Park > Assignee: Chiwan Park > Labels: ML > > Add distance measure interface to calculate distance between two vectors and > some implementations of the interface. In FLINK-1745, [~till.rohrmann] > suggests a interface following: > {code} > trait DistanceMeasure { > def distance(a: Vector, b: Vector): Double > } > {code} > I think that following list of implementation is sufficient to provide first > to ML library users. > * Manhattan distance [1] > * Cosine distance [2] > * Euclidean distance (and Squared) [3] > * Tanimoto distance [4] > * Minkowski distance [5] > * Chebyshev distance [6] > [1]: http://en.wikipedia.org/wiki/Taxicab_geometry > [2]: http://en.wikipedia.org/wiki/Cosine_similarity > [3]: http://en.wikipedia.org/wiki/Euclidean_distance > [4]: > http://en.wikipedia.org/wiki/Jaccard_index#Tanimoto_coefficient_.28extended_Jaccard_coefficient.29 > [5]: http://en.wikipedia.org/wiki/Minkowski_distance > [6]: http://en.wikipedia.org/wiki/Chebyshev_distance -- This message was sent by Atlassian JIRA (v6.3.4#6332)