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Till Rohrmann updated FLINK-1729: --------------------------------- Assignee: hoa nguyen (was: Till Rohrmann) > Assess performance of classification algorithms > ----------------------------------------------- > > Key: FLINK-1729 > URL: https://issues.apache.org/jira/browse/FLINK-1729 > Project: Flink > Issue Type: New Feature > Components: Machine Learning Library > Reporter: Till Rohrmann > Assignee: hoa nguyen > Labels: ML > > In order to validate Flink's classification algorithms (in terms of > performance and accuracy), we should run them on publicly available > classification data sets. This will not only serve as a proof for the > correctness of the implementations but will also show how easy the machine > learning library can be used. > Bottou [1] published some results for the RCV1 dataset using SVMs for > classification. The SVMs are trained using stochastic gradient descent. Thus, > they would be a good comparison for the CoCoA trained SVMs. > Some more benchmark results and publicly available data sets ca be found here > [2]. > Resources: > [1] [http://leon.bottou.org/projects/sgd] > [2] [https://github.com/BIDData/BIDMach/wiki/Benchmarks] -- This message was sent by Atlassian JIRA (v6.3.4#6332)