GaussianMixtureModel (Spark 3.5.5 JavaDoc) (original) (raw)

• Object

• • org.apache.spark.mllib.clustering.GaussianMixtureModel

• All Implemented Interfaces:
  java.io.Serializable, Saveable

public class GaussianMixtureModel
extends Object
implements scala.Serializable, Saveable
Multivariate Gaussian Mixture Model (GMM) consisting of k Gaussians, where points are drawn from each Gaussian i=1..k with probability w(i); mu(i) and sigma(i) are the respective mean and covariance for each Gaussian distribution i=1..k.
param: weights Weights for each Gaussian distribution in the mixture, where weights(i) is the weight for Gaussian i, and weights.sum == 1 param: gaussians Array of MultivariateGaussian where gaussians(i) represents the Multivariate Gaussian (Normal) Distribution for Gaussian i
See Also:
Serialized Form

• • Constructor Summary

  Constructors

  Constructor and Description
  GaussianMixtureModel(double[] weights,MultivariateGaussian[] gaussians)

  • Method Summary

  All Methods Static Methods Instance Methods Concrete Methods

  Modifier and Type	Method and Description
  MultivariateGaussian[]	gaussians()
  int	k() Number of gaussians in mixture
  static GaussianMixtureModel	load(SparkContext sc, String path)
  JavaRDD	predict(JavaRDD<Vector> points) Java-friendly version of predict()
  RDD	predict(RDD<Vector> points) Maps given points to their cluster indices.
  int	predict(Vector point) Maps given point to its cluster index.
  RDD<double[]>	predictSoft(RDD<Vector> points) Given the input vectors, return the membership value of each vector to all mixture components.
  double[]	predictSoft(Vector point) Given the input vector, return the membership values to all mixture components.
  void	save(SparkContext sc, String path) Save this model to the given path.
  double[]	weights()

     * ### Methods inherited from class Object  
     `equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

• • Constructor Detail

     * #### GaussianMixtureModel  
     public GaussianMixtureModel(double[] weights,  
                                 [MultivariateGaussian](../../../../../org/apache/spark/mllib/stat/distribution/MultivariateGaussian.html "class in org.apache.spark.mllib.stat.distribution")[] gaussians)  

  • Method Detail

    * #### load  
    public static [GaussianMixtureModel](../../../../../org/apache/spark/mllib/clustering/GaussianMixtureModel.html "class in org.apache.spark.mllib.clustering") load([SparkContext](../../../../../org/apache/spark/SparkContext.html "class in org.apache.spark") sc,  
                                            String path)  
    * #### weights  
    public double[] weights()  
    * #### gaussians  
    public [MultivariateGaussian](../../../../../org/apache/spark/mllib/stat/distribution/MultivariateGaussian.html "class in org.apache.spark.mllib.stat.distribution")[] gaussians()  
    * #### save  
    public void save([SparkContext](../../../../../org/apache/spark/SparkContext.html "class in org.apache.spark") sc,  
                     String path)  
    Description copied from interface: `[Saveable](../../../../../org/apache/spark/mllib/util/Saveable.html#save-org.apache.spark.SparkContext-java.lang.String-)`  
    Save this model to the given path.  
     This saves: - human-readable (JSON) model metadata to path/metadata/ - Parquet formatted data to path/data/  
     The model may be loaded using `Loader.load`.  
    Specified by:  
    `[save](../../../../../org/apache/spark/mllib/util/Saveable.html#save-org.apache.spark.SparkContext-java.lang.String-)` in interface `[Saveable](../../../../../org/apache/spark/mllib/util/Saveable.html "interface in org.apache.spark.mllib.util")`  
    Parameters:  
    `sc` \- Spark context used to save model data.  
    `path` \- Path specifying the directory in which to save this model. If the directory already exists, this method throws an exception.  
    * #### k  
    public int k()  
    Number of gaussians in mixture  
    Returns:  
    (undocumented)  
    * #### predict  
    public [RDD](../../../../../org/apache/spark/rdd/RDD.html "class in org.apache.spark.rdd")<Object> predict([RDD](../../../../../org/apache/spark/rdd/RDD.html "class in org.apache.spark.rdd")<[Vector](../../../../../org/apache/spark/mllib/linalg/Vector.html "interface in org.apache.spark.mllib.linalg")> points)  
    Maps given points to their cluster indices.  
    Parameters:  
    `points` \- (undocumented)  
    Returns:  
    (undocumented)  
    * #### predict  
    public int predict([Vector](../../../../../org/apache/spark/mllib/linalg/Vector.html "interface in org.apache.spark.mllib.linalg") point)  
    Maps given point to its cluster index.  
    Parameters:  
    `point` \- (undocumented)  
    Returns:  
    (undocumented)  
    * #### predict  
    public [JavaRDD](../../../../../org/apache/spark/api/java/JavaRDD.html "class in org.apache.spark.api.java")<Integer> predict([JavaRDD](../../../../../org/apache/spark/api/java/JavaRDD.html "class in org.apache.spark.api.java")<[Vector](../../../../../org/apache/spark/mllib/linalg/Vector.html "interface in org.apache.spark.mllib.linalg")> points)  
    Java-friendly version of `predict()`  
    Parameters:  
    `points` \- (undocumented)  
    Returns:  
    (undocumented)  
    * #### predictSoft  
    public [RDD](../../../../../org/apache/spark/rdd/RDD.html "class in org.apache.spark.rdd")<double[]> predictSoft([RDD](../../../../../org/apache/spark/rdd/RDD.html "class in org.apache.spark.rdd")<[Vector](../../../../../org/apache/spark/mllib/linalg/Vector.html "interface in org.apache.spark.mllib.linalg")> points)  
    Given the input vectors, return the membership value of each vector to all mixture components.  
    Parameters:  
    `points` \- (undocumented)  
    Returns:  
    (undocumented)  
    * #### predictSoft  
    public double[] predictSoft([Vector](../../../../../org/apache/spark/mllib/linalg/Vector.html "interface in org.apache.spark.mllib.linalg") point)  
    Given the input vector, return the membership values to all mixture components.  
    Parameters:  
    `point` \- (undocumented)  
    Returns:  
    (undocumented)