public class GaussianMixtureModel extends Object implements scala.Serializable, Saveable
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
| Constructor and Description | 
|---|
| GaussianMixtureModel(double[] weights,
                    MultivariateGaussian[] gaussians) | 
| Modifier and Type | Method and Description | 
|---|---|
| MultivariateGaussian[] | gaussians() | 
| int | k()Number of gaussians in mixture | 
| static GaussianMixtureModel | load(SparkContext sc,
    String path) | 
| JavaRDD<Integer> | predict(JavaRDD<Vector> points)Java-friendly version of  predict() | 
| RDD<Object> | 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() | 
public GaussianMixtureModel(double[] weights,
                            MultivariateGaussian[] gaussians)
public static GaussianMixtureModel load(SparkContext sc, String path)
public double[] weights()
public MultivariateGaussian[] gaussians()
public void save(SparkContext sc, String path)
SaveableThis saves: - human-readable (JSON) model metadata to path/metadata/ - Parquet formatted data to path/data/
 The model may be loaded using Loader.load.
 
public int k()
public RDD<Object> predict(RDD<Vector> points)
points - (undocumented)public int predict(Vector point)
point - (undocumented)public JavaRDD<Integer> predict(JavaRDD<Vector> points)
predict()points - (undocumented)public RDD<double[]> predictSoft(RDD<Vector> points)
points - (undocumented)public double[] predictSoft(Vector point)
point - (undocumented)