Package org.apache.spark.mllib.stat

Class KernelDensity

Object

org.apache.spark.mllib.stat.KernelDensity

All Implemented Interfaces:

Serializable

public class KernelDensity
extends Object
implements Serializable

Kernel density estimation. Given a sample from a population, estimate its probability density function at each of the given evaluation points using kernels. Only Gaussian kernel is supported.

Scala example:

 val sample = sc.parallelize(Seq(0.0, 1.0, 4.0, 4.0))
 val kd = new KernelDensity()
   .setSample(sample)
   .setBandwidth(3.0)
 val densities = kd.estimate(Array(-1.0, 2.0, 5.0))
 

See Also:

• Serialized Form

Constructor Summary

Constructors

Constructor	Description
KernelDensity()

Method Summary

Modifier and Type	Method	Description
double[]	estimate(double[] points)	Estimates probability density function at the given array of points.
static double	normPdf(double mean, double standardDeviation, double logStandardDeviationPlusHalfLog2Pi, double x)	Evaluates the PDF of a normal distribution.
KernelDensity	setBandwidth(double bandwidth)	Sets the bandwidth (standard deviation) of the Gaussian kernel (default: 1.0).
KernelDensity	setSample(JavaRDD<Double> sample)	Sets the sample to use for density estimation (for Java users).
KernelDensity	setSample(RDD<Object> sample)	Sets the sample to use for density estimation.

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

KernelDensity

public KernelDensity()

Method Details

normPdf

public static double normPdf(double mean,
 double standardDeviation,
 double logStandardDeviationPlusHalfLog2Pi,
 double x)

Evaluates the PDF of a normal distribution.

setBandwidth

public KernelDensity setBandwidth(double bandwidth)

Sets the bandwidth (standard deviation) of the Gaussian kernel (default: 1.0).

Parameters:

bandwidth - (undocumented)

Returns:

(undocumented)

setSample

public KernelDensity setSample(RDD<Object> sample)

Sets the sample to use for density estimation.

Parameters:

sample - (undocumented)

Returns:

(undocumented)

setSample

public KernelDensity setSample(JavaRDD<Double> sample)

Sets the sample to use for density estimation (for Java users).

Parameters:

sample - (undocumented)

Returns:

(undocumented)

estimate

public double[] estimate(double[] points)

Estimates probability density function at the given array of points.

Parameters:

points - (undocumented)

Returns:

(undocumented)