# 概率符号说明

## 概率符号说明

* [返回顶层目录](https://luweikxy.gitbook.io/machine-learning-notes/statistics-and-information-theory/pages/-LpO5vE88qYwjk5WM_Qf#目录)
* [返回上层目录](/machine-learning-notes/statistics-and-information-theory.md)
* \[u(x;a,b)中的分号";"]\(#u(x;a,b)中的分号";")
* \[p(Y=y|X=x)中的竖线"|"]\(#p(Y=y|X=x)中的竖线"|")

## u(x;a,b)中的分号";"

表示**函数以分后后面的内容为参数**。

我们使用函数$u(x;a,b)$表示实数区间上的均匀分布，其中a和b是区间的端点且满足b>a。符号“;”表&#x793A;**“以什么为参数”**；我们把x作为函数的自变量，a和b作为定义函数的参数。即在\[a,b]内，有$u(x;a,b)=\frac{1}{b-a}$。

## p(Y=y|X=x)中的竖线"|"

表示**条件概率**。

我们将给定X=x,Y=y发生的条件概率记为P(Y=y|X=x)，这个条件概率可以通过下面的公式计算：

$$
P(Y=y|X=x)=\frac{P(Y=y,X=x)}{P(X=x)}
$$


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://luweikxy.gitbook.io/machine-learning-notes/statistics-and-information-theory/probability-symbol-explaination.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
