Github user MechCoder commented on the pull request:
https://github.com/apache/spark/pull/6383#issuecomment-104984400
Note: In master
import org.apache.commons.math3.distribution.NormalDistribution
import org.apache.spark.mllib.stat.KernelDensity
val rdd = sc.parallelize(Array(5.0))
val evaluationPoints = Array(5.0, 6.0)
val densities = new
KernelDensity().setSample(rdd).setBandwidth(3.0).estimate(evaluationPoints)
val normal = new NormalDistribution(5.0, 3.0)
densities(0) - normal.density(5.0)
res1: Double = -0.06649038006690546
val rdd = sc.parallelize(Array(5.0, 10.0))
val evaluationPoints = Array(5.0, 6.0)
val densities = new
KernelDensity().setSample(rdd).setBandwidth(3.0).estimate(evaluationPoints)
val normal1 = new NormalDistribution(5.0, 3.0)
val normal2 = new NormalDistribution(10.0, 3.0)
densities(0) - (normal1.density(5.0) + normal2.density(5.0)) / 2
res2: Double = -0.04153495159951512
Hence the tests pass
cc @jkbradley @mengxr
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