Brian created SPARK-21968:
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Summary: Improved KernelDensity support
Key: SPARK-21968
URL: https://issues.apache.org/jira/browse/SPARK-21968
Project: Spark
Issue Type: Improvement
Components: MLlib
Affects Versions: 2.2.0
Reporter: Brian
Related to SPARK-7753. The KernelDensity API still does not provide a way to
specify a kernel as described in the 7753 ticket, and requires the client to
calculate their own optimal bandwidth.
Specifying a kernel could be something like:
def
setKernel(kernel: Function2[Double,Double]): KernelDensity.this.type
There could be something providing the user with a few options for kernels they
could pass here so they don't need to implement each kernel themselves. Here
are some example kernels:
https://en.wikipedia.org/wiki/Kernel_(statistics)#Kernel_functions_in_common_use
functions could also be provided to get more optimal bandwidth settings without
the user needing to calculate it themselves, e.g. the "rule of thumb" and/or
"solve the equation" bandwidth described here:
https://en.wikipedia.org/wiki/Kernel_density_estimation#Bandwidth_selection
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