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machine-learning-python's Introduction

Using Python to implement Machine Learning Algorithms

一些经典机器学习算法的python实现,目前仍在持续补充;

内容简介

  • 机器学习算法
    • 监督学习:
      • 线性回归

        采用batch,mini_batch, sgd三种梯度优化方法,实现线性回归。

      • 局部加权回归

        线性回归算法的扩展,目标函数是加权的最小二乘。

      • 逻辑回归

        采用梯度下降,牛顿法两种优化方法,实现逻辑回归。

      • 高斯判别分析

      • 支持向量机

        采用核技法,基于smo论文伪码实现对线性数据以及非线性数据的分类。

      • 集成算法

        主要实现了Cart树(无剪枝), 随机森林, 未来待补充GBDT/Adaboost。

      • 隐马尔科夫

      • ...

    • 无监督学习:
      • [Kmeans]

      • [高斯混合模型]

    • ...

  • 可视化效果图
    • Example: 逻辑回归
      逻辑回归

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