学习入门

(拟合联合分布，除计算条件分布之外，还可以计算边缘分布等其他信息当样本数量较多时，收敛速度较快能够解决存在隐变量的问题
需要更多的样本与更多的计算
在分类任务上性能一般不如判别模型)不重要，主要是学习

When fitting the joint distribution, besides computing conditional distributions, it can also derive other relevant information such as marginal distributions. When the sample size is large, it exhibits faster convergence speed and can handle problems with latent variables.
It requires more samples and greater computational resources.
Its performance on classification tasks is generally inferior to that of discriminative models. This content is not critical; the primary goal is for learning purposes.

搜集汇总

背景与挑战

背景概述

该数据集名为“学习入门”，主要用于学习目的，目前因平台维护升级，下载服务暂时不可用。数据集中包含一个图片文件。