Uses of Class
org.ojalgo.data.cluster.Point
Packages that use Point
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Uses of Point in org.ojalgo.data.cluster
Classes in org.ojalgo.data.cluster that implement interfaces with type arguments of type PointModifier and TypeClassDescriptionclassFacade for clustering objects represented by float feature vectors.final classImmutable coordinate point used by the clustering utilities.Fields in org.ojalgo.data.cluster with type parameters of type PointModifier and TypeFieldDescriptionprivate final GeneralisedKMeans<Point> AutomaticClusterer.myClustererprivate final GreedyClustering<Point> GreedyClusterer.myClustererprivate final GeneralisedKMeans<Point> KMeansClusterer.myClustererprivate final RandomClustering<Point> KMeansClusterer.myInitialiserMethods in org.ojalgo.data.cluster that return PointModifier and TypeMethodDescription(package private) PointPointDistanceCache.centroid(Collection<Point> cluster) Pick the centroid for this cluster (one of its current members)Point.Factory.newPoint(float... coordinates) static PointPoint.of(int id, float... coordinates) Creates a point with the supplied id and coordinates (no defensive copy).Methods in org.ojalgo.data.cluster that return types with arguments of type PointModifier and TypeMethodDescription(package private) Function<Collection<Point>, Point> FeatureBasedClusterer.centroid()Returns a function that computes the centroid of a collection of points.(package private) Function<Collection<Point>, Point> FeatureBasedClusterer.centroid()Returns a function that computes the centroid of a collection of points.AutomaticClusterer.cluster(Collection<Point> input) GreedyClusterer.cluster(Collection<Point> input) KMeansClusterer.cluster(Collection<Point> input) SpectralClusterer.cluster(Collection<Point> input) (package private) ToDoubleBiFunction<Point, Point> FeatureBasedClusterer.distance()Returns a function that computes the distance between two points.(package private) ToDoubleBiFunction<Point, Point> FeatureBasedClusterer.distance()Returns a function that computes the distance between two points.(package private) Function<Collection<Point>, List<Point>> FeatureBasedClusterer.initialiser()Returns a function that generates an initial set of centroids from the input points.(package private) Function<Collection<Point>, List<Point>> FeatureBasedClusterer.initialiser()Returns a function that generates an initial set of centroids from the input points.PointDistanceCache.initialiser(Collection<Point> input) Generate an initial set of centroidsMethods in org.ojalgo.data.cluster with parameters of type PointModifier and TypeMethodDescriptionint(package private) doubleReturns the distance between two points.doublePoint.distance(DistanceMeasure measure, Point other) Distance using the suppliedDistanceMeasure.(package private) doubleGet the distance between these two points.Method parameters in org.ojalgo.data.cluster with type arguments of type PointModifier and TypeMethodDescription(package private) PointPointDistanceCache.centroid(Collection<Point> cluster) Pick the centroid for this cluster (one of its current members)AutomaticClusterer.cluster(Collection<Point> input) GreedyClusterer.cluster(Collection<Point> input) KMeansClusterer.cluster(Collection<Point> input) SpectralClusterer.cluster(Collection<Point> input) PointDistanceCache.initialiser(Collection<Point> input) Generate an initial set of centroidsstatic double[]Point.mean(Collection<Point> points) (package private) voidFeatureBasedClusterer.setup(Collection<Point> input) Prepares the internal distance cache for the given input points and distance measure.(package private) voidPointDistanceCache.setup(Collection<Point> input, DistanceMeasure measure) Set up the cache (configure this instance)