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Brian Gawalt commented on SPARK-2335:
-------------------------------------
I'm inclined to wonder the same thing; generalizing beyond integers would
be nice
> k-Nearest Neighbor classification and regression for MLLib
> ----------------------------------------------------------
>
> Key: SPARK-2335
> URL: https://issues.apache.org/jira/browse/SPARK-2335
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Reporter: Brian Gawalt
> Priority: Minor
> Labels: features
>
> The k-Nearest Neighbor model for classification and regression problems is a simple and
intuitive approach, offering a straightforward path to creating non-linear decision/estimation
contours. It's downsides -- high variance (sensitivity to the known training data set) and
computational intensity for estimating new point labels -- both play to Spark's big data strengths:
lots of data mitigates data concerns; lots of workers mitigate computational latency.
> We should include kNN models as options in MLLib.
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