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machine-learning's Introduction

machine-learning

机器学习的重要示例, 偏工程应用.

说明

  • lr_basic: 基于sklearn的LR分类
  • lr_matlib: 将sklearn LR分类效果用matlib绘制出来
  • lr_spark: 基于spark ml完成分布式训练, 模型保存到hdfs
  • lr_pmml: 基于spark ml完成分布式训练, 模型导出pmml文件, 供跨语言加载(主要是JAVA)

依赖

  • python3
  • numpy
  • scipy
  • pandas: 用于dataframe处理
  • matplotlib: 用于绘图
  • sklearn: 单机机器学习算法
  • pyspark: 分布式机器学习算法
  • pyspark2pmml: 将spark ml的模型导出为pmml格式
  • JPMML-SparkML: 支持spark ml模型转换pmml格式的jar包（下载对应spark版本的JPMML-SparkML uber-JAR file）

运行注意

JPMML-SparkML jar

我为spark2.3下载的版本：jpmml-sparkml-executable-1.4.5.jar，放置在当前目录.

导出环境变量

export PYSPARK_PYTHON=/usr/local/bin/python3

这影响spark计算时用哪个版本的Python.

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