spark 实现XGB花瓣预测（多分类）

最新推荐文章于 2024-01-19 09:24:23 发布

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最新推荐文章于 2024-01-19 09:24:23 发布 · 1k 阅读

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package com.fwmagic.spark.xgboost

import ml.dmlc.xgboost4j.scala.spark.{XGBoostClassificationModel, XGBoostClassifier}
import org.apache.spark.ml.{Pipeline, PipelineModel}
import org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
import org.apache.spark.ml.feature._
import org.apache.spark.ml.tuning.{CrossValidator, ParamGridBuilder}
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.types._

object SparkMLlibPipeline {
    def main(args: Array[String]): Unit = {

        var inputPath: String = ""
        var nativeModelPath = ""
        var pipelineModelPath = ""
        if (args.length == 0) {
            println("Using local path")
            inputPath = "/Users/zz/Desktop/com.zz.spark/spark-ml/skhmagic-spark-mllib/data/xgboost/iris.data"
            nativeModelPath = "/Users/zz/Desktop/com.zz.spark/spark-ml/skhmagic-spark-mllib/model_save/xgboost/native_model"
            pipelineModelPath = "/Users/zz/