Spark中组件Mllib的学习12之密集向量和稀疏向量的生成

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更多代码请见：https://github.com/xubo245/SparkLearning
Spark中组件Mllib的学习之基础概念篇
1解释
mllib生成Vector

2.代码：

/**  * @author xubo  *         ref:Spark MlLib机器学习实战  *         more code:https://github.com/xubo245/SparkLearning  *         more blog:http://blog.csdn.net/xubo245  */package org.apache.spark.mllib.learning.basicimport org.apache.spark.mllib.linalg.Vectors/**  * Created by xubo on 2016/5/23.  * Vector  */object VectorLearning {  def main(args: Array[String]) {    val vd = Vectors.dense(2, 0, 6)    println(vd(2))    println(vd)    //数据个数，序号，value    val vs = Vectors.sparse(4, Array(0, 1, 2, 3), Array(9, 5, 2, 7))    println(vs(2))    println(vs)    val vs2 = Vectors.sparse(4, Array(0, 2, 1, 3), Array(9, 5, 2, 7))    println(vs2(2))    println(vs2)  }}

3.结果：

6.0[2.0,0.0,6.0]2.0(4,[0,1,2,3],[9.0,5.0,2.0,7.0])5.0(4,[0,2,1,3],[9.0,5.0,2.0,7.0])

参考
【1】http://spark.apache.org/docs/1.5.2/mllib-guide.html
【2】http://spark.apache.org/docs/1.5.2/programming-guide.html
【3】https://github.com/xubo245/SparkLearning

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