<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[playgoon2的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/playgoon2</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; playgoon2]]></copyright><item><title><![CDATA[信息熵知乎解释，感觉很好，帮助理解决策树算法]]></title><link>https://blog.youkuaiyun.com/playgoon2/article/details/78368149</link><guid>https://blog.youkuaiyun.com/playgoon2/article/details/78368149</guid><author>playgoon2</author><pubDate>Fri, 27 Oct 2017 19:17:15 +0800</pubDate><description><![CDATA[信息熵，决策树核心内容通俗解释]]></description><category></category></item><item><title><![CDATA[kaggle-泰塔尼克号-GBDT-快速分析]]></title><link>https://blog.youkuaiyun.com/playgoon2/article/details/78099647</link><guid>https://blog.youkuaiyun.com/playgoon2/article/details/78099647</guid><author>playgoon2</author><pubDate>Tue, 26 Sep 2017 16:13:35 +0800</pubDate><description><![CDATA[kaggle-泰塔尼克号-GBDT-快速分析]]></description><category></category></item><item><title><![CDATA[python算法和数据结构笔记--python下堆栈的实现及其应用]]></title><link>https://blog.youkuaiyun.com/playgoon2/article/details/77980860</link><guid>https://blog.youkuaiyun.com/playgoon2/article/details/77980860</guid><author>playgoon2</author><pubDate>Thu, 14 Sep 2017 15:18:15 +0800</pubDate><description><![CDATA[python下堆栈的实现及其应用]]></description><category></category></item><item><title><![CDATA[python—matplotlib数据可视化实例注解系列-----设置标注字体样式（matplotlib颜色库）]]></title><link>https://blog.youkuaiyun.com/playgoon2/article/details/77965650</link><guid>https://blog.youkuaiyun.com/playgoon2/article/details/77965650</guid><author>playgoon2</author><pubDate>Wed, 13 Sep 2017 14:32:23 +0800</pubDate><description><![CDATA[python—matplotlib数据可视化实例注解系列-----设置标注字体样式（matplotlib颜色库）]]></description><category></category></item><item><title><![CDATA[python—matplotlib数据可视化实例注解系列-----之柱状图]]></title><link>https://blog.youkuaiyun.com/playgoon2/article/details/77930013</link><guid>https://blog.youkuaiyun.com/playgoon2/article/details/77930013</guid><author>playgoon2</author><pubDate>Mon, 11 Sep 2017 09:57:11 +0800</pubDate><description><![CDATA[python—matplotlib数据可视化实例注解系列-----之柱状图]]></description><category></category></item><item><title><![CDATA[python算法和数据结构笔记--汉诺塔问题超详细递归过程图解（堆栈数据结构）]]></title><link>https://blog.youkuaiyun.com/playgoon2/article/details/77867339</link><guid>https://blog.youkuaiyun.com/playgoon2/article/details/77867339</guid><author>playgoon2</author><pubDate>Wed, 06 Sep 2017 15:45:11 +0800</pubDate><description><![CDATA[汉诺塔问题超详细递归过程图解，在python下利用堆栈实现了递归算法。]]></description><category></category></item><item><title><![CDATA[python—matplotlib数据可视化实例注解系列-----之箱状图]]></title><link>https://blog.youkuaiyun.com/playgoon2/article/details/77737398</link><guid>https://blog.youkuaiyun.com/playgoon2/article/details/77737398</guid><author>playgoon2</author><pubDate>Thu, 31 Aug 2017 09:56:52 +0800</pubDate><description><![CDATA[python—matplotlib数据可视化实例注解系列-----之箱状图]]></description><category></category></item><item><title><![CDATA[python算法和数据结构笔记--递归--二分查找]]></title><link>https://blog.youkuaiyun.com/playgoon2/article/details/77731779</link><guid>https://blog.youkuaiyun.com/playgoon2/article/details/77731779</guid><author>playgoon2</author><pubDate>Thu, 31 Aug 2017 08:59:44 +0800</pubDate><description><![CDATA[python算法和数据结构笔记--递归--二分查找]]></description><category></category></item><item><title><![CDATA[python算法和数据结构笔记--递归--英国标尺的绘制]]></title><link>https://blog.youkuaiyun.com/playgoon2/article/details/77716448</link><guid>https://blog.youkuaiyun.com/playgoon2/article/details/77716448</guid><author>playgoon2</author><pubDate>Wed, 30 Aug 2017 15:22:03 +0800</pubDate><description><![CDATA[python算法和数据结构笔记--递归--英国标尺的绘制]]></description><category></category></item><item><title><![CDATA[python—matplotlib数据可视化实例注解系列-----之函数图]]></title><link>https://blog.youkuaiyun.com/playgoon2/article/details/77668682</link><guid>https://blog.youkuaiyun.com/playgoon2/article/details/77668682</guid><author>playgoon2</author><pubDate>Tue, 29 Aug 2017 09:57:30 +0800</pubDate><description><![CDATA[本例主要介绍了函数图像的显示方法，x，y轴显示范围设置等，帮助学习和查询。]]></description><category></category></item><item><title><![CDATA[Kmeans聚类算法在python下的实现--附测试数据]]></title><link>https://blog.youkuaiyun.com/playgoon2/article/details/77579757</link><guid>https://blog.youkuaiyun.com/playgoon2/article/details/77579757</guid><author>playgoon2</author><pubDate>Fri, 25 Aug 2017 16:41:19 +0800</pubDate><description><![CDATA[Kmeans聚类算法在python下的实现--附测试数据]]></description><category></category></item><item><title><![CDATA[python—matplotlib数据可视化实例注解系列-----之plot图线型设置]]></title><link>https://blog.youkuaiyun.com/playgoon2/article/details/77530347</link><guid>https://blog.youkuaiyun.com/playgoon2/article/details/77530347</guid><author>playgoon2</author><pubDate>Thu, 24 Aug 2017 15:13:51 +0800</pubDate><description><![CDATA[matplotlib中plot图线型设置实例注解]]></description><category></category></item><item><title><![CDATA[python—matplotlib数据可视化实例注解系列-----之函数填充]]></title><link>https://blog.youkuaiyun.com/playgoon2/article/details/77497504</link><guid>https://blog.youkuaiyun.com/playgoon2/article/details/77497504</guid><author>playgoon2</author><pubDate>Wed, 23 Aug 2017 09:23:20 +0800</pubDate><description><![CDATA[plot图中函数填充的方法实例。]]></description><category></category></item><item><title><![CDATA[python—matplotlib数据可视化实例注解系列-----之横条图]]></title><link>https://blog.youkuaiyun.com/playgoon2/article/details/77482767</link><guid>https://blog.youkuaiyun.com/playgoon2/article/details/77482767</guid><author>playgoon2</author><pubDate>Tue, 22 Aug 2017 17:11:40 +0800</pubDate><description><![CDATA[matplotlib显示横条图的实例。]]></description><category></category></item><item><title><![CDATA[BP神经网络计算过程详解，算一遍弄懂反向传播--Python计算过程]]></title><link>https://blog.youkuaiyun.com/playgoon2/article/details/77449450</link><guid>https://blog.youkuaiyun.com/playgoon2/article/details/77449450</guid><author>playgoon2</author><pubDate>Mon, 21 Aug 2017 14:31:42 +0800</pubDate><description><![CDATA[演示BP神经网络计算过程，反向传播的计算过程，帮助理解神经网络工作原理，算一遍就能懂。]]></description><category></category></item><item><title><![CDATA[PCA降维以及Kmeans聚类实例----python,sklearn,PCA,Kmeans]]></title><link>https://blog.youkuaiyun.com/playgoon2/article/details/77326045</link><guid>https://blog.youkuaiyun.com/playgoon2/article/details/77326045</guid><author>playgoon2</author><pubDate>Thu, 17 Aug 2017 14:13:26 +0800</pubDate><description><![CDATA[PCA 算法也叫主成分分析（principal components analysis），主要是用于数据降维的。关于降维，可以这样理解，一组数据有n个feature（客户年龄，收入，每个月消费额度等等），每一个feature有一系列的观测点。而这n个feature中有一些存在线性相关，比如对于某些群体而言，收入和消费是线性相关的。此时我们进行多维度数据分析时只需要考虑其中一个参数就可以足够了，这样]]></description><category></category></item><item><title><![CDATA[Python线性回归实例--Python,sklearn,LinearRegression]]></title><link>https://blog.youkuaiyun.com/playgoon2/article/details/77162219</link><guid>https://blog.youkuaiyun.com/playgoon2/article/details/77162219</guid><author>playgoon2</author><pubDate>Mon, 14 Aug 2017 15:30:40 +0800</pubDate><description><![CDATA[Python sklearn中的LinearRegreesion实例]]></description><category></category></item><item><title><![CDATA[通过实例快速掌握sklearn中的kmeans聚类----python数据分析,聚类,pandas]]></title><link>https://blog.youkuaiyun.com/playgoon2/article/details/77097146</link><guid>https://blog.youkuaiyun.com/playgoon2/article/details/77097146</guid><author>playgoon2</author><pubDate>Fri, 11 Aug 2017 14:25:04 +0800</pubDate><description><![CDATA[本文重点介绍KMeans在python数据分析的实现，快速掌握利用sklearn实现聚类分析的操作方法，先会用在应用中进一步理解内涵也是一种学习途径。]]></description><category></category></item><item><title><![CDATA[拉格朗日插值法在数据分析中的应用——Python插值scimpy,lagrange]]></title><link>https://blog.youkuaiyun.com/playgoon2/article/details/77051285</link><guid>https://blog.youkuaiyun.com/playgoon2/article/details/77051285</guid><author>playgoon2</author><pubDate>Thu, 10 Aug 2017 15:06:55 +0800</pubDate><description><![CDATA[版权声明：本文为博主原创文章，未经博主允许不得转载。
数据分析时，数据清理是一个重要的环节，处理缺失值是常见问题。处理方法可分为三类，删除记录、插值和不处理。这里介绍用拉格朗日插值方法以及在python数据分析中的实现。
拉格朗日插值法是根据已知的点求取函数对未知点进行插值，具体细节这里不做具体介绍，想了解的朋友可以去数数值分析的内容。这里以应用为主，介绍scimpy中的lagrange（）函]]></description><category></category></item><item><title><![CDATA[用Excel演示python中pandas中数据的查询显示方法-python数据分析入门]]></title><link>https://blog.youkuaiyun.com/playgoon2/article/details/76985159</link><guid>https://blog.youkuaiyun.com/playgoon2/article/details/76985159</guid><author>playgoon2</author><pubDate>Wed, 09 Aug 2017 14:15:57 +0800</pubDate><description><![CDATA[版权声明：本文为博主原创文章，未经博主允许不得转载。
       pandas是python进行数据分析必须掌握的基本技能。对于许多初学者而言,pandas中最基本的loc,iloc,at,iat等查询方法十分容易混淆。对于体量较小的数据而言excel能较好进行数据分析、整理工作，对于大多数数据工作者对excel都十分的熟悉。为了能更好的理解pandas的查询操作，这里选用excel作为对比材]]></description><category></category></item></channel></rss>