I will re-implementing the serialization in C++ Thanks a lot.
-----邮件原件----- 发件人: Ted Dunning [mailto:[email protected]] 发送时间: 2011年7月6日 10:48 收件人: [email protected] 主题: Re: How could I use bayse model with my C++ online classifier Well, PMML is the (complicated) standard solution. Otherwise, a Naive Bayes model would probably fit as CSV data. But seriously, it isn't that hard to read a sequence file. Re-implementing our serialization in C++ would be generally useful as well. On Tue, Jul 5, 2011 at 7:38 PM, Lance Norskog <[email protected]> wrote: > Is there a standard text format that would support this data? ARFF, > for example? > > > > On Mon, Jul 4, 2011 at 7:57 PM, beneo_7 <[email protected]> wrote: > > read the java source code and implemenet it in c++ > > > > 我也不明白为啥你要用阿里巴巴的邮箱 > > > > 2011-07-05 > > > > > > > > beneo_7 > > > > > > > > 发件人: 刘逸哲 <[email protected]> > > 发送时间: 2011-07-05 10:55 > > 主 题: How could I use bayse model with my C++ online classifier > > 收件人: "[email protected]" <[email protected]> > > > > > > > > Hi all, > > I have trained a bayes model using mahout on my hadoop > > cluster, > and I want to use this model with my c++ online application. So I will > implement the classifier as mahout did, but I don’t know how to load > the model using c++ as the model are sequence files. > > I want a bayes model in text file, so that I can easily read and > > parse > it using c++. Is there any suggestion about this? > > > > > > > > > > > > ________________________________ > > This email (including any attachments) is confidential and may be > > legally > privileged. If you received this email in error, please delete it > immediately and do not copy it or use it for any purpose or disclose > its contents to any other person. Thank you. > > > > > 本电邮(包括任何附件)可能含有机密资料并受法律保护。如您不是正确的收件人，请您立即删除本邮件。请不要将本电邮进行复制并用作任何其他用途、或透 > 露本邮件之内容。谢谢。 > > > > -- > Lance Norskog > [email protected] > This email (including any attachments) is confidential and may be legally privileged. If you received this email in error, please delete it immediately and do not copy it or use it for any purpose or disclose its contents to any other person. Thank you. 本电邮(包括任何附件)可能含有机密资料并受法律保护。如您不是正确的收件人，请您立即删除本邮件。请不要将本电邮进行复制并用作任何其他用途、或透露本邮件之内容。谢谢。
