[jira] [Commented] (FLINK-1745) Add exact k-nearest-neighbours algorithm to machine learning library

["ASF GitHub Bot (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/FLINK-1745?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15149173#comment-15149173 ] 

ASF GitHub Bot commented on FLINK-1745:
---------------------------------------

Github user danielblazevski commented on the pull request:

    https://github.com/apache/flink/pull/1220#issuecomment-184847163
  
    Hi @chiwanpark sorry for the delay!  I will now have more time to wrap this PR up.  I added a check just before calling `knn`:
    ```scala
                      if (useQuadTree) {
                        if (metric.isInstanceOf[EuclideanDistanceMetric] ||
                          metric.isInstanceOf[SquaredEuclideanDistanceMetric]){
                          knnQueryWithQuadTree(training.values, testing.values, k, metric, queue, out)
                        } else {
                          throw new IllegalArgumentException(s" Error: metric must be" +
                            s" Euclidean or SquaredEuclidean!")
                        }
                      } else {
                        knnQueryBasic(training.values, testing.values, k, metric, queue, out)
                      }
                    }
                  }
                }
    ```
    Does that work?  The commit includes the hint for the cross operation as well. 


> 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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