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a tiny data analyst

A tiny data analyst. Tuesday, June 1, 2010. Prior and Posterior probability. UserID LabelID Prior Likelihood Posterior. 1 1 71/206 15/71 .07. 1 2 27/206 2/27 .009. 1 3 108/206 1/108 .004. 2 1 71/206 21/71 .101. 2 2 27/206 15/27 .07. 2 3 108/206 7/108 .03. 3 1 71/206 35/71 .169. 3 2 27/206 0/27 0. 3 3 108/206 100/108 .485. 4 1 71/206 0/71 0. 4 2 27/206 10/27 .04. 4 3 108/206 0/108 0. Posterior = Prior * Likehood(category). 71/206 * 15/71 = .07. View on Google Sidewiki. Wednesday, April 28, 2010. 因为我有SSH&#...

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A tiny data analyst. Tuesday, June 1, 2010. Prior and Posterior probability. UserID LabelID Prior Likelihood Posterior. 1 1 71/206 15/71 .07. 1 2 27/206 2/27 .009. 1 3 108/206 1/108 .004. 2 1 71/206 21/71 .101. 2 2 27/206 15/27 .07. 2 3 108/206 7/108 .03. 3 1 71/206 35/71 .169. 3 2 27/206 0/27 0. 3 3 108/206 100/108 .485. 4 1 71/206 0/71 0. 4 2 27/206 10/27 .04. 4 3 108/206 0/108 0. Posterior = Prior * Likehood(category). 71/206 * 15/71 = .07. View on Google Sidewiki. Wednesday, April 28, 2010. 因为我有SSH&#...

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9 淘宝商城情况和定位淘宝cfo商城主管张勇

10 同时它必须要符合一定的资质要求，

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a tinydata analyst,tinydata,no comments,email this,blogthis,share to twitter,share to facebook,share to pinterest,淘宝商城情况和定位淘宝cfo商城主管张勇,同时它必须要符合一定的资质要求，,实行更严格的管理规则和对商家更严重的服务要求,怎么样在这里面找到所在商品品牌的目标用户，,怎么样对这些目标用户进行定向营销”,数据挖掘可以做的事情：分析淘宝用户的购物需求，,为企业提供需求分析,hive

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a tiny data analyst | tinydata.blogspot.com Reviews

https://tinydata.blogspot.com

A tiny data analyst. Tuesday, June 1, 2010. Prior and Posterior probability. UserID LabelID Prior Likelihood Posterior. 1 1 71/206 15/71 .07. 1 2 27/206 2/27 .009. 1 3 108/206 1/108 .004. 2 1 71/206 21/71 .101. 2 2 27/206 15/27 .07. 2 3 108/206 7/108 .03. 3 1 71/206 35/71 .169. 3 2 27/206 0/27 0. 3 3 108/206 100/108 .485. 4 1 71/206 0/71 0. 4 2 27/206 10/27 .04. 4 3 108/206 0/108 0. Posterior = Prior * Likehood(category). 71/206 * 15/71 = .07. View on Google Sidewiki. Wednesday, April 28, 2010. 因为我有SSH&#...

INTERNAL PAGES

tinydata.blogspot.com

1

a tiny data analyst: Clusters on Twitter users

http://tinydata.blogspot.com/2009/10/clusters-on-twitter-users.html

A tiny data analyst. Tuesday, October 27, 2009. Clusters on Twitter users. Using kmeans method to extract the clusters. Comtain : common people , geek,profession manager,online addict.any more. Also supply a result. A Twitter users segmentation". Data into results A Twitter users segmentation. View on Google Sidewiki. Subscribe to: Post Comments (Atom). Clusters on Twitter users. Stanford opencourse data mining . 12298;Pro MySql》关于随机主键对InnoDB插入性能的影响. Mysql exclusive locked Bug. Go to where .

2

a tiny data analyst: April 2010

http://tinydata.blogspot.com/2010_04_01_archive.html

A tiny data analyst. Wednesday, April 28, 2010. 1：淘宝商城做B2C，相当于一个设防的经济特区，. 要进入这个经济特区经营的商家，必须是企业，. 2：淘宝商城的情况：20个淘宝商城（分类），. 12000家商户，吸引点是：1.9亿注册会员，中国的网名3. 3：商家/ 企业在淘宝商城的定位很重要，“1. 4：电子商务非常重要的问题是后台问题，即电子商务的解决方案，. 比如配货，例子：一个商家做活动一天得配送4W个包裹，“. 怎么样进行流程设计，能够保证这些包裹能够很好的报，. In reference to: 图文：淘宝商城主管张勇演讲互联网科技时代新浪网. View on Google Sidewiki. Wednesday, April 21, 2010. Hive 是由Facebook found的一个Hadoop子项目，看. Http:/ wiki.apache.org/hadoop/Hive/GettingStarted#Hive introduction videos From Cloudera.

3

a tiny data analyst: February 2009

http://tinydata.blogspot.com/2009_02_01_archive.html

A tiny data analyst. Thursday, February 26, 2009. 首先要些吸引人球的东西，要用户自己主动在网站注册ID，比如这个网站要有些很牛逼的东西，比如一些新的专辑分享，或者一些很难找到的东西，别人在google或百度搜到这网站有，那就体现出网站的独立性和个性，别人才能记住这个网站。那比如一些精品东西分享要放在显要位置，要系统性，让别人好找。标题要做得炫一点, 标题那一块搞大点,吸引人，比如这个http:/ www.haibao.cn/，标题栏方面就做得比较好，体现出品牌效应。主要页面上还要提供些在线听歌，要比较抓耳，比如一些用户纯粹就是网站去找歌的，这方面不要担心，我可以试试，这方面的素材我很多，不如我博客上推荐音乐方面就比较受欢迎，到时候要给我些专区。疑问是：到底是先做大，然后完善，还是反过来呢？自己水平有限，如果要很好的完善，那么网站发展速度就会因为我而停滞。 Subscribe to: Posts (Atom). View my complete profile.

4

a tiny data analyst: October 2009

http://tinydata.blogspot.com/2009_10_01_archive.html

A tiny data analyst. Tuesday, October 27, 2009. What funny is follow. SAS Base does the great job there. SPSS Modeler as well. SPSS Statistic trial is available at http:/ www.spss.com. Java is cool. But you are wasting time with programming. Data-miner has more important task to do than generating tons of code. I disagree for two reasons:. I disagree for two reasons:. I cannot count the algorithms I can give you a understandable description of in 1 minute, but when it comes to a real data analysis you wi...

5

a tiny data analyst: November 2009

http://tinydata.blogspot.com/2009_11_01_archive.html

A tiny data analyst. Wednesday, November 25, 2009. 3 dimensions on Behaviral targeting. CRM Dimension : Customer Retention. Branding Dimension : Brandwashing. Direct response : Customer Acquisition. In reference to: http:/ www.clickz.com/3401511. View on Google Sidewiki. Subscribe to: Posts (Atom). 3 dimensions on Behaviral targeting. View my complete profile.

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a tiny data analyst

A tiny data analyst. Tuesday, June 1, 2010. Prior and Posterior probability. UserID LabelID Prior Likelihood Posterior. 1 1 71/206 15/71 .07. 1 2 27/206 2/27 .009. 1 3 108/206 1/108 .004. 2 1 71/206 21/71 .101. 2 2 27/206 15/27 .07. 2 3 108/206 7/108 .03. 3 1 71/206 35/71 .169. 3 2 27/206 0/27 0. 3 3 108/206 100/108 .485. 4 1 71/206 0/71 0. 4 2 27/206 10/27 .04. 4 3 108/206 0/108 0. Posterior = Prior * Likehood(category). 71/206 * 15/71 = .07. View on Google Sidewiki. Wednesday, April 28, 2010. 因为我有SSH&#...

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