Xiangrui Meng created SPARK-7753:
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Summary: Improve kernel density API
Key: SPARK-7753
URL: https://issues.apache.org/jira/browse/SPARK-7753
Project: Spark
Issue Type: Sub-task
Components: MLlib
Affects Versions: 1.4.0
Reporter: Xiangrui Meng
Assignee: Xiangrui Meng
Kernel density estimation is provided in many statistics libraries:
http://en.wikipedia.org/wiki/Kernel_density_estimation#Statistical_implementation.
We should make sure that we implement a similar API. The two most important
parameters of kernel density estimation are kernel type and bandwidth. Besides
density estimation, it is also used for smoothing. The current API is designed
only for Gaussian kernel and density estimation:
{code}
def kernelDensity(samples: RDD[Double], standardDeviation: Double,
evaluationPoints: Iterable[Double]): Array[Double]
{code}
It would be nice if we can come up with an extensible API.
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