public class LocalKMeans
extends Object
| Constructor and Description | 
|---|
LocalKMeans()  | 
| Modifier and Type | Method and Description | 
|---|---|
static void | 
initializeForcefully(boolean isInterpreter,
                    boolean silent)  | 
static org.apache.spark.mllib.clustering.VectorWithNorm[] | 
kMeansPlusPlus(int seed,
              org.apache.spark.mllib.clustering.VectorWithNorm[] points,
              double[] weights,
              int k,
              int maxIterations)
Run K-means++ on the weighted point set  
points. | 
static void | 
org$apache$spark$internal$Logging$$log__$eq(org.slf4j.Logger x$1)  | 
static org.slf4j.Logger | 
org$apache$spark$internal$Logging$$log_()  | 
public static org.apache.spark.mllib.clustering.VectorWithNorm[] kMeansPlusPlus(int seed,
                                                                                org.apache.spark.mllib.clustering.VectorWithNorm[] points,
                                                                                double[] weights,
                                                                                int k,
                                                                                int maxIterations)
points. This first does the K-means++
 initialization procedure and then rounds of Lloyd's algorithm.seed - (undocumented)points - (undocumented)weights - (undocumented)k - (undocumented)maxIterations - (undocumented)public static org.slf4j.Logger org$apache$spark$internal$Logging$$log_()
public static void org$apache$spark$internal$Logging$$log__$eq(org.slf4j.Logger x$1)
public static void initializeForcefully(boolean isInterpreter,
                                        boolean silent)