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ASF GitHub Bot commented on FLINK-1735: --------------------------------------- GitHub user ChristophAl opened a pull request: https://github.com/apache/flink/pull/665 [FLINK-1735] Feature Hasher The prototype of the feature hasher. - The implementation is based on the scikit-learn feature hasher - Test vectors have been generated by scikit-learn as well - Currently the implementation only works on Seq[String] You can merge this pull request into a Git repository by running: $ git pull https://github.com/ChristophAl/flink FLINK-1735_FeatureHasher Alternatively you can review and apply these changes as the patch at: https://github.com/apache/flink/pull/665.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #665 ---- commit e5ad7e842f443dd4b15fe21f3d1d89c238c882d1 Author: Christoph Alt <christoph....@posteo.de> Date: 2015-05-06T22:10:24Z Initial commit Issue #1735 commit 1e9312fdc46b741faea6bdfb26fc4ce359cd1cfa Author: Christoph Alt <christoph....@posteo.de> Date: 2015-05-08T13:54:53Z Added basic testcase for FeatureHasher commit a0c6ee6251edc4d0e556ba98886a783a072bd27b Author: Christoph Alt <christoph....@posteo.de> Date: 2015-05-08T13:58:59Z FeatureHasher prototype - Added a prototype of Feature Hasher, currently accepts Seq[String] only commit c55eb11fa21943dd8451256755bc707a59c3f5d3 Author: Christoph Alt <christoph....@posteo.de> Date: 2015-05-08T14:09:48Z Corrected typos commit 7002ab9e18a6cca5b55d700967accb375538faad Author: Christoph Alt <christoph....@posteo.de> Date: 2015-05-09T14:25:42Z Moved Featurehasher to feature.extraction package commit 15b868f08806b375fff564f851f668122d363457 Author: Christoph Alt <christoph....@posteo.de> Date: 2015-05-09T14:31:19Z Readded FeatureHasher.scala commit 38e0650ebdec305c4a51e788699da0809a3b1973 Author: Christoph Alt <christoph....@posteo.de> Date: 2015-05-09T18:36:00Z Reformated test vectors ---- > Add FeatureHasher to machine learning library > --------------------------------------------- > > Key: FLINK-1735 > URL: https://issues.apache.org/jira/browse/FLINK-1735 > Project: Flink > Issue Type: New Feature > Components: Machine Learning Library > Reporter: Till Rohrmann > Assignee: Felix Neutatz > Labels: ML > > Using the hashing trick [1,2] is a common way to vectorize arbitrary feature > values. The hash of the feature value is used to calculate its index for a > vector entry. In order to mitigate possible collisions, a second hashing > function is used to calculate the sign for the update value which is added to > the vector entry. This way, it is likely that collision will simply cancel > out. > A feature hasher would also be helpful for NLP problems where it could be > used to vectorize bag of words or ngrams feature vectors. > Resources: > [1] [https://en.wikipedia.org/wiki/Feature_hashing] > [2] > [http://scikit-learn.org/stable/modules/feature_extraction.html#feature-extraction] -- This message was sent by Atlassian JIRA (v6.3.4#6332)