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https://issues.apache.org/jira/browse/FLINK-1745?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15149198#comment-15149198
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ASF GitHub Bot commented on FLINK-1745:
---------------------------------------
Github user danielblazevski commented on the pull request:
https://github.com/apache/flink/pull/1220#issuecomment-184853357
P.S. about rebasing, need to be careful, something went wrong the first
time around. I actually just started working on a new laptop, and started the
git repo "from scratch" as follows:
```
clone the master and FLINK-1745 branches of my fork of Flink
checkout FLINK-1745, commit and push to origin (origin = my fork)
```
I set upstream to `origin`, is that a mistake? Namely, when I push
locally to GitHub, I set `upstream` to `origin`, namely I ran:
```
git push --set-upstream origin FLINK-1745
```
`origin` is my fork. Should I re-do this by adding a new `remote` called
`apache` and run
```
git push --set-upstream apache FLINK-1745
```
and then run the git commands you mentioned to rebase? Want to be careful,
making a re-basing mistake can be a nightmare to fix :-)
> Add exact k-nearest-neighbours algorithm to machine learning library
> --------------------------------------------------------------------
>
> Key: FLINK-1745
> URL: https://issues.apache.org/jira/browse/FLINK-1745
> Project: Flink
> Issue Type: New Feature
> Components: Machine Learning Library
> Reporter: Till Rohrmann
> Assignee: Daniel Blazevski
> Labels: ML, Starter
>
> Even though the k-nearest-neighbours (kNN) [1,2] algorithm is quite trivial
> it is still used as a mean to classify data and to do regression. This issue
> focuses on the implementation of an exact kNN (H-BNLJ, H-BRJ) algorithm as
> proposed in [2].
> Could be a starter task.
> Resources:
> [1] [http://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm]
> [2] [https://www.cs.utah.edu/~lifeifei/papers/mrknnj.pdf]
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