<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[fangwc的专栏]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/fangwc</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; fangwc]]></copyright><item><title><![CDATA[安装intelij + scala + sbt，手动、离线、公司]]></title><link>https://blog.youkuaiyun.com/fangwc/article/details/53940506</link><guid>https://blog.youkuaiyun.com/fangwc/article/details/53940506</guid><author>fangwc</author><pubDate>Fri, 30 Dec 2016 10:54:56 +0800</pubDate><description><![CDATA[公司上班，开发环境是在虚拟桌面 ，离线环境下配置intelij 需要手动安装 scala、sbt 插件。
intelij要对应固定的插件版本
我的是： ideaIC-2016.2.5 + idea-sbt-plugin-1.8.0+ scala-intellij-bin-2016.2.1
intelij 下载地址：https://confluence.jetbrains.com/displa]]></description><category></category></item><item><title><![CDATA[spark -运行]]></title><link>https://blog.youkuaiyun.com/fangwc/article/details/52457335</link><guid>https://blog.youkuaiyun.com/fangwc/article/details/52457335</guid><author>fangwc</author><pubDate>Wed, 07 Sep 2016 10:41:18 +0800</pubDate><description><![CDATA[spark运行机制]]></description><category></category></item><item><title><![CDATA[python 爬虫 beautifulsoup  example 例子]]></title><link>https://blog.youkuaiyun.com/fangwc/article/details/51192057</link><guid>https://blog.youkuaiyun.com/fangwc/article/details/51192057</guid><author>fangwc</author><pubDate>Tue, 19 Apr 2016 16:56:23 +0800</pubDate><description><![CDATA[今天第一次用python的beautifulsoup，虽然比较生疏，但还是爬下来了。
爬的网站是： 网站排行
爬取的内容：包括网站的url, aleax排名，百度权重， PR等
import urllib2
import pandas as pd
from bs4 import BeautifulSoup

def urlprocess(url):
    u = url.replace(']]></description><category></category></item><item><title><![CDATA[python pandas 函数累积]]></title><link>https://blog.youkuaiyun.com/fangwc/article/details/51178150</link><guid>https://blog.youkuaiyun.com/fangwc/article/details/51178150</guid><author>fangwc</author><pubDate>Mon, 18 Apr 2016 11:14:47 +0800</pubDate><description><![CDATA[pandas.min
http://stackoverflow.com/questions/25479607/pandas-min-of-selected-row-and-columns]]></description><category></category></item><item><title><![CDATA[Hadoop，Spark和Storm]]></title><link>https://blog.youkuaiyun.com/fangwc/article/details/51153724</link><guid>https://blog.youkuaiyun.com/fangwc/article/details/51153724</guid><author>fangwc</author><pubDate>Thu, 14 Apr 2016 17:54:08 +0800</pubDate><description><![CDATA[Hadoop，Spark和Storm




由于Google没有开源Google分布式计算模型的技术实现，所以其他互联网公司只能根据Google三篇技术论文中的相关原理，搭建自己的分布式计算系统。




Yahoo的工程师Doug Cutting和Mike Cafarella在2005年合作开发了分布式计算系统Hadoop。后来，Hadoop被贡献给了Apache基金会，成]]></description><category></category></item><item><title><![CDATA[anaconda conda install 安装包]]></title><link>https://blog.youkuaiyun.com/fangwc/article/details/50965275</link><guid>https://blog.youkuaiyun.com/fangwc/article/details/50965275</guid><author>fangwc</author><pubDate>Tue, 29 Mar 2016 10:02:47 +0800</pubDate><description><![CDATA[linux下加入路径
export PATH=~/anaconda/bin:$PATH
conda install ××]]></description><category></category></item><item><title><![CDATA[one-hot enconding，类别型特征，非数值型特征。]]></title><link>https://blog.youkuaiyun.com/fangwc/article/details/50803460</link><guid>https://blog.youkuaiyun.com/fangwc/article/details/50803460</guid><author>fangwc</author><pubDate>Fri, 04 Mar 2016 16:07:17 +0800</pubDate><description><![CDATA[在计算广告领域，对于CTR,CVR，反作弊等内容时，对于categorical features，时常会用one-hot enconding 的处理方法。
借用互联网已有的博客，
在很多机器学习任务中，特征并不总是连续值，而有可能是分类值。

例如，考虑一下的三个特征：


["male", "female"]

["from Europe", "from US", "from ]]></description><category></category></item></channel></rss>