jasonding1354 / Prml_notes
Licence: mit
该项目是关于机器学习经典书籍《Pattern Recognition and Machine Learning》的学习笔记，我用python实现了书中的一些实例，希望帮助感兴趣的人更好的理解
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PRML_Notes
##项目概要 该项目是关于机器学习经典书籍《Pattern Recognition and Machine Learning》的学习笔记，用python实现了书籍中的大部分实例，希望帮助大家更好的理解抽象的概念和复杂的公式。
##内容目录
1. 概率分布(Probability Distribution)
- 1.1 Binary_Variables——二元变量、伯努利分布、二项式分布、Beta分布作为二项式分布的先验概率分布
- 1.2 Multinomial_Variables——多项式分布、狄利克雷分布
- 1.3 The_Gaussian_Distribution——高斯分布、高斯分布的几何解释
p1. Figaro库的介绍
Figaro是一个构造概率性模型的Scala库。在Figaro中，该模型由任意数量的数据结构（称作“元素”）组成。每个元素代表在您的情境中可取任意数量值的一个变量。这些数据结构用Scala实现，您可以用这些数据结构编写Scala程序创建模型。可以通过关于元素值的信息提供证据，也可以指定希望在查询中了解的元素。至于推理算法，您可以选择一个Figaro内建推理算法并应用到模型上，根据证据回答您的查询。推理算法以Scala实现，其调用就是一个Scala函数调用。推理结果是查询元素不同值的概率。
- Figaro的hello world程序
- Figaro的基本元素介绍 介绍使用Figaro的元素定义常见的概率分布
p2. 使用Figaro编写概率程序
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