程序包 org.apache.flink.ml.clustering.kmeans

类 KMeans

java.lang.Object

org.apache.flink.ml.clustering.kmeans.KMeans

所有已实现的接口:

Serializable, org.apache.flink.ml.api.Estimator<KMeans,KMeansModel>, org.apache.flink.ml.api.Stage<KMeans>, KMeansModelParams<KMeans>, KMeansParams<KMeans>, org.apache.flink.ml.common.param.HasDistanceMeasure<KMeans>, org.apache.flink.ml.common.param.HasFeaturesCol<KMeans>, org.apache.flink.ml.common.param.HasMaxIter<KMeans>, org.apache.flink.ml.common.param.HasPredictionCol<KMeans>, org.apache.flink.ml.common.param.HasSeed<KMeans>, org.apache.flink.ml.param.WithParams<KMeans>

public class KMeans
extends Object
implements org.apache.flink.ml.api.Estimator<KMeans,KMeansModel>, KMeansParams<KMeans>

An Estimator which implements the k-means clustering algorithm.

See https://en.wikipedia.org/wiki/K-means_clustering.

另请参阅:

序列化表格

字段概要

从接口继承的字段 org.apache.flink.ml.common.param.HasDistanceMeasure

DISTANCE_MEASURE

从接口继承的字段 org.apache.flink.ml.common.param.HasFeaturesCol

FEATURES_COL

从接口继承的字段 org.apache.flink.ml.common.param.HasMaxIter

MAX_ITER

从接口继承的字段 org.apache.flink.ml.common.param.HasPredictionCol

PREDICTION_COL

从接口继承的字段 org.apache.flink.ml.common.param.HasSeed

SEED

从接口继承的字段 org.apache.flink.ml.clustering.kmeans.KMeansModelParams

K

从接口继承的字段 org.apache.flink.ml.clustering.kmeans.KMeansParams

INIT_MODE

构造器概要

构造器

构造器	说明
KMeans()

方法概要

修饰符和类型	方法	说明
KMeansModel	fit(org.apache.flink.table.api.Table... inputs)
Map<org.apache.flink.ml.param.Param<?>,Object>	getParamMap()
static KMeans	load(org.apache.flink.table.api.bridge.java.StreamTableEnvironment tEnv, String path)
void	save(String path)
static org.apache.flink.streaming.api.datastream.DataStream<org.apache.flink.ml.linalg.DenseVector[]>	selectRandomCentroids(org.apache.flink.streaming.api.datastream.DataStream<org.apache.flink.ml.linalg.DenseVector> data, int k, long seed)

从类继承的方法 java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

从接口继承的方法 org.apache.flink.ml.common.param.HasDistanceMeasure

getDistanceMeasure, setDistanceMeasure

从接口继承的方法 org.apache.flink.ml.common.param.HasFeaturesCol

getFeaturesCol, setFeaturesCol

从接口继承的方法 org.apache.flink.ml.common.param.HasMaxIter

getMaxIter, setMaxIter

从接口继承的方法 org.apache.flink.ml.common.param.HasPredictionCol

getPredictionCol, setPredictionCol

从接口继承的方法 org.apache.flink.ml.common.param.HasSeed

getSeed, setSeed

从接口继承的方法 org.apache.flink.ml.clustering.kmeans.KMeansModelParams

getK, setK

从接口继承的方法 org.apache.flink.ml.clustering.kmeans.KMeansParams

getInitMode, setInitMode

从接口继承的方法 org.apache.flink.ml.param.WithParams

get, getParam, set

构造器详细资料

KMeans

public KMeans()

方法详细资料

fit

public KMeansModel fit(org.apache.flink.table.api.Table... inputs)

指定者:

fit 在接口中 org.apache.flink.ml.api.Estimator<KMeans,KMeansModel>

save

public void save(String path)
          throws IOException

指定者:

save 在接口中 org.apache.flink.ml.api.Stage<KMeans>

抛出:

IOException

load

public static KMeans load(org.apache.flink.table.api.bridge.java.StreamTableEnvironment tEnv,
                          String path)
                   throws IOException

抛出:

IOException

getParamMap

public Map<org.apache.flink.ml.param.Param<?>,Object> getParamMap()

指定者:

getParamMap 在接口中 org.apache.flink.ml.param.WithParams<KMeans>

selectRandomCentroids

public static org.apache.flink.streaming.api.datastream.DataStream<org.apache.flink.ml.linalg.DenseVector[]> selectRandomCentroids(org.apache.flink.streaming.api.datastream.DataStream<org.apache.flink.ml.linalg.DenseVector> data,
                                                                                                                                   int k,
                                                                                                                                   long seed)