<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[u010844092的专栏]]></title><description><![CDATA[初生牛犊]]></description><link>https://blog.youkuaiyun.com/u010844092</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; u010844092]]></copyright><item><title><![CDATA[OpenMS build 遇到的问题]]></title><link>https://blog.youkuaiyun.com/u010844092/article/details/78596265</link><guid>https://blog.youkuaiyun.com/u010844092/article/details/78596265</guid><author>u010844092</author><pubDate>Tue, 21 Nov 2017 20:02:01 +0800</pubDate><description><![CDATA[主要参考链接：http://ftp.mi.fu-berlin.de/pub/OpenMS/develop-documentation/html/install_win.html
我的平台：VS2013,X64
注意：
1、一定要运行VS2013 x64 Native Tools Command Prompt，要不然会出现32位和64位的错误
2、对于VS2013的generator是：Vi]]></description><category></category></item><item><title><![CDATA[阿里云机器学习平台PAI的视频介绍（其中tensorflow高级教程有tf的代码优化讲解）]]></title><link>https://blog.youkuaiyun.com/u010844092/article/details/78093088</link><guid>https://blog.youkuaiyun.com/u010844092/article/details/78093088</guid><author>u010844092</author><pubDate>Tue, 26 Sep 2017 11:08:14 +0800</pubDate><description><![CDATA[https://tianchi.aliyun.com/competition/new_articleDetail.html?spm=5176.9876270.0.0.65d0a126iwqolt&raceId=&postsId=1515]]></description><category></category></item><item><title><![CDATA[外网连接内网的centos mysql数据库]]></title><link>https://blog.youkuaiyun.com/u010844092/article/details/78057362</link><guid>https://blog.youkuaiyun.com/u010844092/article/details/78057362</guid><author>u010844092</author><pubDate>Thu, 21 Sep 2017 21:51:37 +0800</pubDate><description><![CDATA[1、首先按照下边的连接在centos服务器上进行设置。主要设置远程连接的用户信息，以及打开mysql端口3306的监听
http://www.fantxi.com/blog/archives/enable-remote-access-mysql-centos/

2、设置内网中路由器的端口映射]]></description><category></category></item><item><title><![CDATA[rcnn网络学习资料整理]]></title><link>https://blog.youkuaiyun.com/u010844092/article/details/77655672</link><guid>https://blog.youkuaiyun.com/u010844092/article/details/77655672</guid><author>u010844092</author><pubDate>Mon, 28 Aug 2017 20:50:09 +0800</pubDate><description><![CDATA[一、Selective Search for Object Recognition：
1、首先得到一些小的初始化区域，方法参考：http://blog.sciencenet.cn/blog-261330-722530.html
2、在存在的区域中找出相似性最大的两个区域合并，重复此步骤直到最后就剩下一个区域
参考链接：
http://blog.youkuaiyun.com/charwing/artic]]></description><category></category></item><item><title><![CDATA[ubuntu16.04 安装搜狗输入法]]></title><link>https://blog.youkuaiyun.com/u010844092/article/details/74129919</link><guid>https://blog.youkuaiyun.com/u010844092/article/details/74129919</guid><author>u010844092</author><pubDate>Sun, 02 Jul 2017 16:34:25 +0800</pubDate><description><![CDATA[http://www.voidcn.com/blog/qq_21792169/article/p-6307484.html]]></description><category></category></item><item><title><![CDATA[matlab read excel出错]]></title><link>https://blog.youkuaiyun.com/u010844092/article/details/73303045</link><guid>https://blog.youkuaiyun.com/u010844092/article/details/73303045</guid><author>u010844092</author><pubDate>Thu, 15 Jun 2017 22:06:01 +0800</pubDate><description><![CDATA[错误：
服务器异常
解决办法：
将excel中com加载项全都去掉]]></description><category></category></item><item><title><![CDATA[python with...as语法理解]]></title><link>https://blog.youkuaiyun.com/u010844092/article/details/63686194</link><guid>https://blog.youkuaiyun.com/u010844092/article/details/63686194</guid><author>u010844092</author><pubDate>Sun, 19 Mar 2017 17:15:38 +0800</pubDate><description><![CDATA[http://zhoutall.com/archives/325]]></description><category></category></item><item><title><![CDATA[python 生成器和迭代器的区别]]></title><link>https://blog.youkuaiyun.com/u010844092/article/details/63685908</link><guid>https://blog.youkuaiyun.com/u010844092/article/details/63685908</guid><author>u010844092</author><pubDate>Sun, 19 Mar 2017 16:55:23 +0800</pubDate><description><![CDATA[https://segmentfault.com/a/1190000002900850]]></description><category></category></item><item><title><![CDATA[vmware tools在ubuntu-16.04.2-desktop-amd64安装失败]]></title><link>https://blog.youkuaiyun.com/u010844092/article/details/62889721</link><guid>https://blog.youkuaiyun.com/u010844092/article/details/62889721</guid><author>u010844092</author><pubDate>Fri, 17 Mar 2017 15:57:34 +0800</pubDate><description><![CDATA[Failure to install VMware Tools: Cannot find the answer BINDIR in the installer database (1013159)

解决办法：https://kb.vmware.com/selfservice/microsites/search.do?language=en_US&cmd=displayKC&externalI]]></description><category></category></item><item><title><![CDATA[PCA降维 SVD参考链接]]></title><link>https://blog.youkuaiyun.com/u010844092/article/details/59669848</link><guid>https://blog.youkuaiyun.com/u010844092/article/details/59669848</guid><author>u010844092</author><pubDate>Thu, 02 Mar 2017 20:45:55 +0800</pubDate><description><![CDATA[http://blog.youkuaiyun.com/panhubo/article/details/51971081
https://www.zhihu.com/question/22237507

http://www.cnblogs.com/LeftNotEasy/archive/2011/01/19/svd-and-applications.html]]></description><category></category></item><item><title><![CDATA[PCA降维的一些思考]]></title><link>https://blog.youkuaiyun.com/u010844092/article/details/59483735</link><guid>https://blog.youkuaiyun.com/u010844092/article/details/59483735</guid><author>u010844092</author><pubDate>Thu, 02 Mar 2017 11:18:30 +0800</pubDate><description><![CDATA[参考：http://blog.youkuaiyun.com/xiaojidan2011/article/details/11595869
我觉得参考网址里有句话说的很好，矩阵*矩阵的含义：右边矩阵的每个列向量在左边矩阵的行向量的投影变换。
原矩阵设置为A(m*n)，B为寻找的降维矩阵，C为A降维后的矩阵
PCA降维实际就是寻找一个矩阵B，使得A在这个矩阵变换后的矩阵C（即C=B*A），投影字段内的方差最]]></description><category></category></item><item><title><![CDATA[linux环境下hadoop安装遇到的问题及解决办法]]></title><link>https://blog.youkuaiyun.com/u010844092/article/details/54970399</link><guid>https://blog.youkuaiyun.com/u010844092/article/details/54970399</guid><author>u010844092</author><pubDate>Fri, 10 Feb 2017 14:49:13 +0800</pubDate><description><![CDATA[Java安装时，在~/.bashrc设置环境变量，其他环境变量也是
 
出错：javac -classpath hadoop-*-core.jar -d playground/classes playground/src/WordCount.java
Hadoop2.7用的common中的jar，没有-core.jar。用bin/Hadoop classpath查看应该含有的路径，将这些路径]]></description><category></category></item><item><title><![CDATA[线性回归的一些思考（SVM）]]></title><link>https://blog.youkuaiyun.com/u010844092/article/details/53729627</link><guid>https://blog.youkuaiyun.com/u010844092/article/details/53729627</guid><author>u010844092</author><pubDate>Sun, 18 Dec 2016 20:39:28 +0800</pubDate><description><![CDATA[1、对于线性回归模型的代价函数，为了能应用求导来求其最小值（代价函数可导），不能用错误的分类个数作为代价函数（不可导）又或者用S函数（非凸函数，不能应用梯度下降，转化为log凸函数），简单的做法就是转化为距离（统计学习方法书中提到的）或者机器学习课堂上讲到的几种形式，这些形式都可导。
2、线性模型中，对于简单的代价函数是可以直接求导得到（比如机器学习课堂上讲的简单线性回归模型），但是一般都采用梯]]></description><category></category></item><item><title><![CDATA[one hot coding]]></title><link>https://blog.youkuaiyun.com/u010844092/article/details/53165327</link><guid>https://blog.youkuaiyun.com/u010844092/article/details/53165327</guid><author>u010844092</author><pubDate>Mon, 14 Nov 2016 22:19:28 +0800</pubDate><description><![CDATA[主要是将原类别特征分解为数字0或者1的特征，这样原来的特征将变得稀疏化，取1的时候，表示属于某一类，取0表示不属于某一类
下边链接是详细介绍：http://blog.youkuaiyun.com/dulingtingzi/article/details/51374487]]></description><category></category></item><item><title><![CDATA[RStudio 调试]]></title><link>https://blog.youkuaiyun.com/u010844092/article/details/52886288</link><guid>https://blog.youkuaiyun.com/u010844092/article/details/52886288</guid><author>u010844092</author><pubDate>Fri, 21 Oct 2016 18:56:08 +0800</pubDate><description><![CDATA[https://support.rstudio.com/hc/en-us/articles/205612627-Debugging-with-RStudio]]></description><category></category></item><item><title><![CDATA[模逆元，扩展欧几里德算法详解]]></title><link>https://blog.youkuaiyun.com/u010844092/article/details/52870105</link><guid>https://blog.youkuaiyun.com/u010844092/article/details/52870105</guid><author>u010844092</author><pubDate>Thu, 20 Oct 2016 10:54:47 +0800</pubDate><description><![CDATA[http://blog.youkuaiyun.com/zhjchengfeng5/article/details/7786595]]></description><category></category></item><item><title><![CDATA[方差，偏差的区别]]></title><link>https://blog.youkuaiyun.com/u010844092/article/details/50628914</link><guid>https://blog.youkuaiyun.com/u010844092/article/details/50628914</guid><author>u010844092</author><pubDate>Wed, 03 Feb 2016 12:42:01 +0800</pubDate><description><![CDATA[一目了然的图：
https://www.zhihu.com/question/20448464

公式推导：
http://blog.youkuaiyun.com/xmsheji/article/details/38871137

http://www.cnblogs.com/LeftNotEasy/archive/2010/12/19/mathmatic_in_machine_learning_]]></description><category></category></item><item><title><![CDATA[神经网络-反向传播算法]]></title><link>https://blog.youkuaiyun.com/u010844092/article/details/50628487</link><guid>https://blog.youkuaiyun.com/u010844092/article/details/50628487</guid><author>u010844092</author><pubDate>Wed, 03 Feb 2016 11:09:28 +0800</pubDate><description><![CDATA[推导过程：
http://www.mamicode.com/info-detail-671452.html]]></description><category></category></item><item><title><![CDATA[html jsp中<video>无法播放视频，该视频是由xuggler压缩图片流形成的]]></title><link>https://blog.youkuaiyun.com/u010844092/article/details/50491202</link><guid>https://blog.youkuaiyun.com/u010844092/article/details/50491202</guid><author>u010844092</author><pubDate>Sun, 10 Jan 2016 08:55:55 +0800</pubDate><description><![CDATA[无法播放视频，原因暂时未知。但是可用下边链接中的方法，在jsp中播放xuggler压缩的视频
http://blog.youkuaiyun.com/muzizhuben/article/details/7183798
但是这个控件播放有限制，目前我测试只能在IE中播放]]></description><category></category></item><item><title><![CDATA[xuggle 多张图片转换为视频]]></title><link>https://blog.youkuaiyun.com/u010844092/article/details/50407618</link><guid>https://blog.youkuaiyun.com/u010844092/article/details/50407618</guid><author>u010844092</author><pubDate>Sat, 26 Dec 2015 10:24:55 +0800</pubDate><description><![CDATA[代码：
writer.encodeVideo(0, img, System.nanoTime() - startTime,TimeUnit.NANOSECONDS);
出现以下错误：
could not resample from BGR24 to YUV420P for picture of type BGR24；
错误原因：图片和视频的长宽不一致导致无法转换]]></description><category></category></item></channel></rss>