Scala学习笔记

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数据类型

操作

在Spark上的应用

案例

Beta分布随机数

Bayes平滑计算CTR先验

Bayes平滑计算CTR先验

class entity(traindata: RDD[Array[Double]], outputPath: String) extends serializable {        var a: Double = 1.0        var b: Double = 1.0        var da: Double = a        var db: Double = b        var index = 0        def calculate(): Unit = {            while (index < 1000 && da > 1.0E-9 && db > 1.0E-9) {                var x1 = 0.0                var y1 = 0.0                var x2 = 0.0                traindata.foreach(point => {                    x1 += MBLAS.digamma(point(2) + 1 + a) - MBLAS.digamma(a)                    y1 += MBLAS.digamma(point(1) + 1 + a + b) - MBLAS.digamma(a + b)                    x2 += MBLAS.digamma(point(1) - point(2) + b) - MBLAS.digamma(b)                    val na = a                    val nb = b                    a *= (x1 / y1)                    b *= (x2 / y1)                    da = Math.abs(a - na)                    db = Math.abs(b - nb)                })            }        }        println(a, b)        analyseLog.append("---------bayes smooth---------\n")        analyseLog.append("a=" + a).append("\n")        analyseLog.append("b=" + b).append("\n")        MUtils.saveString(fs, analyseLog.toString, outputPath + "/bayes_smooth")    }

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