Apache spark 为什么可以'；在Spark KMeans算法上设置ε=1e-4？

我想通过设置

epsilon=1e-4

而不是设置

numIterations

来训练Spark上的K-means模型。在spark shell中，我输入：

val model = KMeans.train(trainRDD, numClusters=8, runs=30, initializationMode="k-means||",epsilon=1e-4)

但是错误，错误信息如下：

scala> val model = KMeans.train(trainRDD, numClusters=8, runs=30, initializationMode="k-means||",epsilon=1e-4)
<console>:48: error: overloaded method value train with alternatives:
  (data: org.apache.spark.rdd.RDD[org.apache.spark.mllib.linalg.Vector],k: Int,maxIterations: Int,runs: Int)org.apache.spark.mllib.clustering.KMeansModel <and>
  (data: org.apache.spark.rdd.RDD[org.apache.spark.mllib.linalg.Vector],k: Int,maxIterations: Int)org.apache.spark.mllib.clustering.KMeansModel <and>
  (data: org.apache.spark.rdd.RDD[org.apache.spark.mllib.linalg.Vector],k: Int,maxIterations: Int,runs: Int,initializationMode: String)org.apache.spark.mllib.clustering.KMeansModel <and>
  (data: org.apache.spark.rdd.RDD[org.apache.spark.mllib.linalg.Vector],k: Int,maxIterations: Int,runs: Int,initializationMode: String,seed: Long)org.apache.spark.mllib.clustering.KMeansModel
 cannot be applied to (org.apache.spark.rdd.RDD[org.apache.spark.mllib.linalg.Vector], numClusters: Int, runs: Int, initializationMode: String, epsilon: Double)
       val model = KMeans.train(trainRDD, numClusters=8, runs=30, initializationMode="k-means||",epsilon=1e-4)
                          ^

scala>val model=KMeans.train（trainRDD，numClusters=8，runs=30，initializationMode=“k-means | |”，epsilon=1e-4）
：48：错误：重载方法值序列和备选方案：
（数据：org.apache.spark.rdd.rdd[org.apache.spark.mllib.linalg.Vector]，k:Int，maxIterations:Int，runs:Int）org.apache.spark.mllib.clustering.KMeansModel
（数据：org.apache.spark.rdd.rdd[org.apache.spark.mllib.linalg.Vector]，k:Int，maxIterations:Int）org.apache.spark.mllib.clustering.KMeansModel
（数据：org.apache.spark.rdd.rdd[org.apache.spark.mllib.linalg.Vector]，k:Int，maxIterations:Int，runs:Int，initializationMode:String）org.apache.spark.mllib.clustering.KMeansModel
（数据：org.apache.spark.rdd.rdd[org.apache.spark.mllib.linalg.Vector]，k:Int，maxIterations:Int，runs:Int，initializationMode:String，seed:Long）org.apache.spark.mllib.clustering.KMeansModel
无法应用于（org.apache.spark.rdd.rdd[org.apache.spark.mllib.linalg.Vector]，numClusters:Int，runs:Int，initializationMode:String，epsilon:Double）
val model=KMeans.train（trainRDD，numClusters=8，runs=30，initializationMode=“k-means | | |”，epsilon=1e-4）
^

---

我该怎么办

没有定义此类

列车

方法

使用实构造函数，并根据需要设置参数

请参阅文档：

---

然后使用

setEpsilon

设置提前终止阈值。

尝试setEpsilon方法如何操作@croxy@kiseliu怎么做什么？