On-line machine learning packages?
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.