[R] On-line machine learning packages?

[Jason Edgecombe]

Hello Jay,

Did you find the answer to your question on incremental machine 
learning? If not, I found some links that might help:

It appears that might be able to do streaming/incremental machine 
learning in Weka:
http://moa.cs.waikato.ac.nz/details/classification/using-weka/

On the above link, there is a link to a free online book on data stream 
mining:
http://heanet.dl.sourceforge.net/project/moa-datastream/documentation/StreamMining.pdf

While weka is a separate project from R, there is an R to Weka interface 
available at
http://cran.r-project.org/web/packages/RWeka/index.html

Sadly, I didn't see any streaming/incremental machine learning packages 
on the CRAN machine leaning task view.

I would guess that your best bet is using Weka with the Rweka interface, 
but I'm a neophyte in the machine learning field, so please take this 
advice with a grain of salt.

Sincerely,
Jason


On 09/13/2011 02:35 AM, Jay wrote:
> How does sequential classification differ form running a one-off
> classifier for each run?
> ->  Because feedback from the previous round can and needs to be
> incorporated into the ext round.
>
>
> http://lmgtfy.com/?q=R+machine+learning
> ->  That is a new low. I was hoping to get help, oblivious I was wrong
> to use this forum in the hopes of somebody had already battled these
> kinds of problems in R.
>
>
> On Sep 13, 1:52 am, Jason Edgecombe<ja... at rampaginggeek.com>  wrote:
>> I already provided the link to the task view, which provides a list of
>> the more popular machine learning algorithms for R.
>>
>> Do you have a particular algorithm or technique in mind? Does it have a
>> name?
>>
>> How does sequential classification differ form running a one-off
>> classifier for each run?
>>
>> On 09/12/2011 05:24 AM, Jay wrote:
>>
>>
>>
>>> In my mind this sequential classification task with feedback is
>>> somewhat different from an completely offline, once-off,
>>> classification. Am I wrong?
>>> However, it looks like the mentality on this topic is to refer me to
>>> cran/google in order to look for solutions myself. Oblivious I know
>>> about these sources, and as I said, I used rseek.org among other
>>> sources to look for solutions. I did not start this topic for fun, I'm
>>> asking for help to find a suitable machine learning packages that
>>> readily incorporates feedback loops and online learning. If somebody
>>> has experience these kinds of problems in R, please respond.
>>> Or will
>>> "http://cran.r-project.org
>>> Look for 'Task Views'"
>>> be my next piece of advice?
>>> On Sep 12, 11:31 am, Dennis Murphy<djmu... at gmail.com>    wrote:
>>>> http://cran.r-project.org/web/views/
>>>> Look for 'machine learning'.
>>>> Dennis
>>>> On Sun, Sep 11, 2011 at 11:33 PM, Jay<josip.2... at gmail.com>    wrote:
>>>>> If the answer is so obvious, could somebody please spell it out?
>>>>> On Sep 11, 10:59 pm, Jason Edgecombe<ja... at rampaginggeek.com>    wrote:
>>>>>> Try this:
>>>>>> http://cran.r-project.org/web/views/MachineLearning.html
>>>>>> On 09/11/2011 12:43 PM, Jay wrote:
>>>>>>> Hi,
>>>>>>> I used the rseek search engine to look for suitable solutions, however
>>>>>>> as I was unable to find anything useful, I'm asking for help.
>>>>>>> Anybody have experience with these kinds of problems? I looked into
>>>>>>> dynaTree, but as information is a bit scares and as I understand it,
>>>>>>> it might not be what I'm looking for..(?)
>>>>>>> BR,
>>>>>>> Jay
>>>>>>> On Sep 11, 7:15 pm, David Winsemius<dwinsem... at comcast.net>      wrote:
>>>>>>>> On Sep 11, 2011, at 11:42 AM, Jay wrote:
>>>>>>>>> What R packages are available for performing classification tasks?
>>>>>>>>> That is, when the predictor has done its job on the dataset (based on
>>>>>>>>> the training set and a range of variables), feedback about the true
>>>>>>>>> label will be available and this information should be integrated for
>>>>>>>>> the next classification round.
>>>>>>>> You should look at CRAN Task Views. Extremely easy to find from the
>>>>>>>> main R-project page.
>>>>>>>> --
>>>>>>>> David Winsemius, MD
>>>>>>>> West Hartford, CT
>>>>>>>> ______________________________________________
>>>>>>>> R-h... at r-project.org mailing listhttps://stat.ethz.ch/mailman/listinfo/r-help
>>>>>>>> PLEASE do read the posting guidehttp://www.R-project.org/posting-guide.html
>>>>>>>> and provide commented, minimal, self-contained, reproducible code.
>>>>>>> ______________________________________________
>>>>>>> R-h... at r-project.org mailing list
>>>>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>>>>> PLEASE do read the posting guidehttp://www.R-project.org/posting-guide.html
>>>>>>> and provide commented, minimal, self-contained, reproducible code.
>>>>>> ______________________________________________
>>>>>> R-h... at r-project.org mailing listhttps://stat.ethz.ch/mailman/listinfo/r-help
>>>>>> PLEASE do read the posting guidehttp://www.R-project.org/posting-guide.html
>>>>>> and provide commented, minimal, self-contained, reproducible code.
>>>>> ______________________________________________
>>>>> R-h... at r-project.org mailing list
>>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>>> PLEASE do read the posting guidehttp://www.R-project.org/posting-guide.html
>>>>> and provide commented, minimal, self-contained, reproducible code.
>>>> ______________________________________________
>>>> R-h... at r-project.org mailing listhttps://stat.ethz.ch/mailman/listinfo/r-help
>>>> PLEASE do read the posting guidehttp://www.R-project.org/posting-guide.html
>>>> and provide commented, minimal, self-contained, reproducible code.
>>> ______________________________________________
>>> R-h... at r-project.org mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guidehttp://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>> ______________________________________________
>> R-h... at r-project.org mailing listhttps://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guidehttp://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>