Uses of Class
edu.umd.cloud9.example.clustering.Point

Packages that use Point

edu.umd.cloud9.example.clustering

Uses of Point in edu.umd.cloud9.example.clustering

Methods in edu.umd.cloud9.example.clustering that return Point

Point	Point.clone()
static Point	UnivariateGaussianMixtureModel.drawRandomPointFromGaussian(PVector L) Draws a point from the considered distribution.
Point[]	UnivariateGaussianMixtureModel.drawRandomPoints(int m) Draws points from the considered mixture model.

Methods in edu.umd.cloud9.example.clustering with parameters of type Point

double	UnivariateGaussianMixtureModel.density(Point x) Computes the density value of this mixture value.
static double	UnivariateGaussianMixtureModel.densityOfGaussian(Point x, PVector param) Computes the density value \f$ f(x;\mu,\sigma^2) \f$.
static UnivariateGaussianMixtureModel	ExpectationMaximization.initialize(Point[] points, double[] means) Initializes the mixture model with points that are closet the given means.
static UnivariateGaussianMixtureModel	ExpectationMaximization.initialize(Point[] points, int n) Initializes the mixture model with random points.
static List<Point>[]	KMeans.run(Point[] points, int k) Performs a k-means on the point set to compute k clusters.
static UnivariateGaussianMixtureModel	ExpectationMaximization.run(Point[] points, UnivariateGaussianMixtureModel m) Performs the Expectation-Maximization algorithm.