Uses of Interface
de.citec.ml.rng.RNGModel

Uses of RNGModel in de.citec.ml.rng

Subinterfaces of RNGModel in de.citec.ml.rng

Modifier and Type	Interface and Description
interface	RNGErrorModel An RNGModel that additionally implements this interface also provides information on the quantization error at each training epoch.

Classes in de.citec.ml.rng that implement RNGModel

Modifier and Type	Class and Description
class	RNGModelImpl This provides a default implementation of the RNGModel interface.

Methods in de.citec.ml.rng with parameters of type RNGModel

Modifier and Type	Method and Description
static int[]	RelationalNeuralGas.classify(double[][] D, RNGModel model) Classifies new data according to a given RNGModel.
static int	RelationalNeuralGas.classify(double[] d, RNGModel model) Classifies a new data point according to a given RNGModel.
static int[]	RelationalNeuralGas.getAssignments(RNGModel model) Returns the strict assignments of all data points handled in the given Relational Neural Gas model to prototypes.
static int[][]	RelationalNeuralGas.getClusterMembers(RNGModel model) Returns an array with K entries, where each entry is another array containing the indices of all data points that have been assigned to the respective cluster/prototype.
static int[]	RelationalNeuralGas.getClusterMembers(RNGModel model, int k) Returns the indices of all data points that have been assigned to the cluster/prototype with index k.
static int[]	RelationalNeuralGas.getClusterMembers(RNGModel model, int k, int[] assignments) Returns the indices of all data points that have been assigned to the cluster/prototype with index k.
static double[][]	RelationalDistances.getDistancesToPrototypes(double[][] D, RNGModel model) Calculates the squared distances of n data points to all prototypes, based on the distances from the test to the training data D and a relational neural gas model.
static double[]	RelationalDistances.getDistancesToPrototypes(double[] d, RNGModel model) Calculates the squared distances of a data point to all prototypes, based on the distances to the training data d and a relational neural gas model.
static int[]	RelationalNeuralGas.getExamplars(RNGModel model) Returns an array with K entries, where entry k is the index of the data point which is closest to the relational prototype for cluster k.