<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[isla77的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/isla77</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; isla77]]></copyright><item><title><![CDATA[kaggle房价预测-回归模型]]></title><link>https://blog.youkuaiyun.com/isla77/article/details/125900871</link><guid>https://blog.youkuaiyun.com/isla77/article/details/125900871</guid><author>isla77</author><pubDate>Sun, 14 Aug 2022 16:44:11 +0800</pubDate><description><![CDATA[第一次做kaggle比赛项目，参考了很多大佬的文章~这是kaggle的一个经典Data Science项目，作为数据分析的新手，房价预测是一个很好的入门练习项目。]]></description><category></category></item><item><title><![CDATA[《机器学习实战》学习笔记第十章-K-means]]></title><link>https://blog.youkuaiyun.com/isla77/article/details/126262723</link><guid>https://blog.youkuaiyun.com/isla77/article/details/126262723</guid><author>isla77</author><pubDate>Wed, 10 Aug 2022 22:08:54 +0800</pubDate><description><![CDATA[聚类是一种无监督学习，事先并不知道要寻找的内容，没有目标变量，只是将相似的对象归到一个簇中。]]></description><category></category></item><item><title><![CDATA[《机器学习实战》学习笔记第九章-树回归]]></title><link>https://blog.youkuaiyun.com/isla77/article/details/126228105</link><guid>https://blog.youkuaiyun.com/isla77/article/details/126228105</guid><author>isla77</author><pubDate>Tue, 09 Aug 2022 17:12:47 +0800</pubDate><description><![CDATA[树回归通过构建决策节点把数据数据切分成区域，然后局部区域进行回归拟合。]]></description><category></category></item><item><title><![CDATA[《机器学习实战》学习笔记第八章-回归]]></title><link>https://blog.youkuaiyun.com/isla77/article/details/126197576</link><guid>https://blog.youkuaiyun.com/isla77/article/details/126197576</guid><author>isla77</author><pubDate>Sun, 07 Aug 2022 22:26:25 +0800</pubDate><description><![CDATA[回归的目的就是预测数值型的目标值。一般线性回归y=w*x+b，回归和线性回归一般是一个意思。]]></description><category></category></item><item><title><![CDATA[《机器学习实战》学习笔记第七章-Adaboost]]></title><link>https://blog.youkuaiyun.com/isla77/article/details/126174322</link><guid>https://blog.youkuaiyun.com/isla77/article/details/126174322</guid><author>isla77</author><pubDate>Sat, 06 Aug 2022 14:59:30 +0800</pubDate><description><![CDATA[集成方法（ensemble method） 通过组合多个学习器来完成学习任务。一般采用的是弱可学习分类器，通过集成方法，组合成一个强可学习分类器。]]></description><category></category></item><item><title><![CDATA[《机器学习实战》学习笔记第六章-支持向量机SVM]]></title><link>https://blog.youkuaiyun.com/isla77/article/details/126097777</link><guid>https://blog.youkuaiyun.com/isla77/article/details/126097777</guid><author>isla77</author><pubDate>Tue, 02 Aug 2022 21:04:50 +0800</pubDate><description><![CDATA[支持向量机是线性分类器，是一种学霸方法，能最大限度分开两个类，即不仅做得对，还要保证质量]]></description><category></category></item><item><title><![CDATA[《机器学习实战》学习笔记第五章-逻辑回归]]></title><link>https://blog.youkuaiyun.com/isla77/article/details/126083192</link><guid>https://blog.youkuaiyun.com/isla77/article/details/126083192</guid><author>isla77</author><pubDate>Sun, 31 Jul 2022 22:43:01 +0800</pubDate><description><![CDATA[用直线拟合的过程称为回归。根据现有数据对分类边界线建立回归公式，以此进行分类的过程即逻辑回归过程。]]></description><category></category></item><item><title><![CDATA[《机器学习实战》学习笔记第四章-朴素贝叶斯]]></title><link>https://blog.youkuaiyun.com/isla77/article/details/126055866</link><guid>https://blog.youkuaiyun.com/isla77/article/details/126055866</guid><author>isla77</author><pubDate>Fri, 29 Jul 2022 22:55:12 +0800</pubDate><description><![CDATA[比较一个确定的点属于不同类别的概率，哪个概率大，属于哪一类。]]></description><category></category></item><item><title><![CDATA[《机器学习实战》学习笔记第三章-决策树]]></title><link>https://blog.youkuaiyun.com/isla77/article/details/126010365</link><guid>https://blog.youkuaiyun.com/isla77/article/details/126010365</guid><author>isla77</author><pubDate>Thu, 28 Jul 2022 22:42:52 +0800</pubDate><description><![CDATA[建立一个树状模型，每个节点筛选出不同结果]]></description><category></category></item><item><title><![CDATA[《机器学习实战》学习笔记第二章-KNN]]></title><link>https://blog.youkuaiyun.com/isla77/article/details/125998003</link><guid>https://blog.youkuaiyun.com/isla77/article/details/125998003</guid><author>isla77</author><pubDate>Tue, 26 Jul 2022 21:46:55 +0800</pubDate><description><![CDATA[以近邻K个点为参考，多数是什么特征，未知点就是什么特征。即采用测量不同特征值直接的距离方法来进行分类。]]></description><category></category></item><item><title><![CDATA[淘宝用户行为分析项目——MySQL数据分析+Tableau可视化]]></title><link>https://blog.youkuaiyun.com/isla77/article/details/125672700</link><guid>https://blog.youkuaiyun.com/isla77/article/details/125672700</guid><author>isla77</author><pubDate>Fri, 08 Jul 2022 16:26:20 +0800</pubDate><description><![CDATA[本项目数据是从阿里巴巴天池下载的一份淘宝用户行为的数据集，用于隐式反馈推荐问题的研究]]></description><category></category></item></channel></rss>