本文整理汇总了Scala中org.apache.spark.mllib.feature类的典型用法代码示例。如果您正苦于以下问题：Scala feature类的具体用法？Scala feature怎么用？Scala feature使用的例子？那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
在下文中一共展示了feature类的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Scala代码示例。
示例1: GloVe
//设置package包名称以及导入依赖的类
package org.apache.spark.ml.feature
import org.apache.spark.ml.Estimator
import org.apache.spark.ml.param.ParamMap
import org.apache.spark.ml.util.{DefaultParamsWritable, Identifiable}
import org.apache.spark.mllib.feature
import org.apache.spark.sql.Dataset
import org.apache.spark.sql.types.StructType
final class GloVe(override val uid: String)
extends Estimator[GloVeModel] with GloVeBase with DefaultParamsWritable {
def this() = this(Identifiable.randomUID("glove"))
def setInputCol(value: String): this.type = set(inputCol, value)
def setOutputCol(value: String): this.type = set(outputCol, value)
def setDim(value: Int): this.type = set(dim, value)
def setAlpha(value: Double): this.type = set(alpha, value)
def setWindow(value: Int): this.type = set(window, value)
def setStepSize(value: Double): this.type = set(stepSize, value)
def setMaxIter(value: Int): this.type = set(maxIter, value)
def setSeed(value: Long): this.type = set(seed, value)
def setMinCount(value: Int): this.type = set(minCount, value)
override def fit(dataset: Dataset[_]): GloVeModel = {
transformSchema(dataset.schema, logging = true)
val input = dataset.select($(inputCol)).rdd.map(_.getAs[Seq[String]](0))
val wordVectors = new feature.GloVe()
.setLearningRate($(stepSize))
.setMinCount($(minCount))
.setNumIterations($(maxIter))
.setSeed($(seed))
.setDim($(dim))
.fit(input)
copyValues(new GloVeModel(uid, wordVectors).setParent(this))
}
override def transformSchema(schema: StructType): StructType = {
validateAndTransformSchema(schema)
}
override def copy(extra: ParamMap): GloVe = defaultCopy(extra)
}