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>, HasDistanceMeasure<KMeans>, HasFeaturesCol<KMeans>, HasMaxIter<KMeans>, HasPredictionCol<KMeans>, 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.clustering.kmeans.KMeansParams

INIT_MODE

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.common.param.HasMaxIter

MAX_ITER

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.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.HasPredictionCol

PREDICTION_COL

构造器概要

构造器

构造器和说明
KMeans()

方法概要

限定符和类型	方法和说明
KMeansModel	fit(org.apache.flink.table.api.Table... inputs)
Map<org.apache.flink.ml.param.Param<?>,Object>	getParamMap()
static KMeans	load(org.apache.flink.streaming.api.environment.StreamExecutionEnvironment env, 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.clustering.kmeans.KMeansParams

getInitMode, setInitMode

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.common.param.HasMaxIter

getMaxIter, setMaxIter

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.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.HasPredictionCol

getPredictionCol, setPredictionCol

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.streaming.api.environment.StreamExecutionEnvironment env,
                          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)