Example usage for Java weka.clusterers SimpleKMeans fields, constructors, methods, implement or subclass
The text is from its open source code.
| SimpleKMeans() the default constructor. |
| void | buildClusterer(Instances data) Generates a clusterer. |
| int | clusterInstance(Instance instance) Classifies a given instance. |
| int[] | getAssignments() Gets the assignments for each instance. |
| Instances | getClusterCentroids() Gets the the cluster centroids. |
| double[][][] | getClusterNominalCounts() Returns for each cluster the weighted frequency counts for the values of each nominal attribute. |
| double[] | getClusterSizes() Gets the sum of weights for all the instances in each cluster. |
| Instances | getClusterStandardDevs() Gets the standard deviations of the numeric attributes in each cluster. |
| DistanceFunction | getDistanceFunction() returns the distance function currently in use. |
| int | getNumClusters() gets the number of clusters to generate. |
| double | getSquaredError() Gets the squared error for all clusters. |
| int | numberOfClusters() Returns the number of clusters. |
| void | setDisplayStdDevs(boolean stdD) Sets whether standard deviations and nominal count. |
| void | setDistanceFunction(DistanceFunction df) sets the distance function to use for instance comparison. |
| void | setDontReplaceMissingValues(boolean r) Sets whether missing values are to be replaced. |
| void | setFastDistanceCalc(boolean value) Sets whether to use faster distance calculation. |
| void | setMaxIterations(int n) set the maximum number of iterations to be executed. |
| void | setNumClusters(int n) set the number of clusters to generate. |
| void | setNumExecutionSlots(int slots) Set the degree of parallelism to use. |
| void | setOptions(String[] options) Parses a given list of options. |
| void | setPreserveInstancesOrder(boolean r) Sets whether order of instances must be preserved. |
| void | setSeed(int value) Set the seed for random number generation. |
| String | toString() return a string describing this clusterer. |