小编pie*_*ada的帖子

我正在使用斯坦福 NER，并且在实体“MISC”中有一些结果

4 class :Location, Person, Organization, Misc

但我不知道什么真正代表了这个实体，有人知道那个实体是什么吗？

谢谢

我试图在scala中定义一个函数,用Spark迭代它.这是我的代码:

import org.apache.spark.{SparkConf, SparkContext}
import org.apache.spark.sql.SQLContext
import org.apache.spark.ml.{Pipeline, PipelineModel}
import org.apache.spark.ml.clustering.KMeans
import org.apache.spark.mllib.linalg.Vectors

import org.apache.spark.ml.feature.VectorIndexer
import org.apache.spark.ml.feature.VectorAssembler
import org.apache.spark.rdd._

    val assembler = new VectorAssembler()
          .setInputCols(Array("feature1", "feature2", "feature3"))
          .setOutputCol("features")
val assembled = assembler.transform(df)

// measures the average distance to centroid, for a model built with a given k.

def clusteringScore(data: RDD[Vector],k:Int) = {

val kmeans = new KMeans()
    .setK(k)
    .setFeaturesCol("features")
    .setPredictionCol("prediction")
    val model = kmeans.fit(data)

  val WSSSE = model.computeCost(data)   println(s"Within Set Sum of Squared Errors = $WSSSE")

}

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