<rss xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title>Deeplearning - 标签 - 研发日志 · R&amp;D Log</title><link>https://rd163.visword.com/tags/deeplearning/</link><description>Deeplearning - 标签 - 研发日志 · R&amp;D Log</description><generator>Hugo -- gohugo.io</generator><language>zh-CN</language><managingEditor>whutluohui@gmail.com (小智晖)</managingEditor><webMaster>whutluohui@gmail.com (小智晖)</webMaster><copyright>本作品采用知识共享署名-非商业性使用 4.0 国际许可协议进行许可。</copyright><lastBuildDate>Sat, 26 Apr 2025 00:00:00 +0800</lastBuildDate><atom:link href="https://rd163.visword.com/tags/deeplearning/" rel="self" type="application/rss+xml"/><item><title>逻辑回归</title><link>https://rd163.visword.com/posts/logistic-regression/</link><pubDate>Sat, 26 Apr 2025 00:00:00 +0800</pubDate><author><name>小智晖</name></author><guid>https://rd163.visword.com/posts/logistic-regression/</guid><description>&lt;p>Logistic Regression 虽然被称为回归，但其实际上是分类模型，并常用于二分类。Logistic Regression 因其简单、可并行化、可解释强深受工业界喜爱。&lt;/p>
&lt;p>Logistic 回归的本质是：假设数据服从这个分布，然后使用极大似然估计做参数的估计。&lt;/p></description></item><item><title>线性回归</title><link>https://rd163.visword.com/posts/linear-regression/</link><pubDate>Sat, 26 Apr 2025 00:00:00 +0800</pubDate><author><name>小智晖</name></author><guid>https://rd163.visword.com/posts/linear-regression/</guid><description>&lt;p>回归（regression）是能为一个或多个自变量与因变量之间关系建模的一类方法。 在自然科学和社会科学领域，回归经常用来表示输入和输出之间的关系。&lt;/p></description></item></channel></rss>