Also, you could get the Mean Square Error from the model summary page which should be a good measurement about the model.
On Mon, Jul 25, 2016 at 4:48 PM, Manolis Vavalis <[email protected]> wrote: > > On Jul 25, 2016, at 4:35 PM, Nirmal Fernando <[email protected]> wrote: > > You can use Random Forest Regression too. It should be more accurate than > linear regression. > > > Good idea. We will try it out right away. > > > Also, can you please explain the use-case? > > > I will ask the interns to describe the use-case on their own words and > comment if required. > > Cheers > > Manolis > > > On Mon, Jul 25, 2016 at 3:40 PM, Nihla Akram <[email protected]> wrote: > >> Hello Srinath, >> >> >> Yes, we used WSO2 ML. >> >> We received some csv files containing the weather and other related data >> from Magda in order to predict the clearing price using WSO2 ML. >> >> Initially we used Linear Regression with the default configurations. >> >> Below is the prediction obtained by changing the Parameter >> configurations. These results are quite close to the initial predicted >> values obtained from Magda. >> >> >> Thanks, >> Nihla >> >> On Mon, Jul 25, 2016 at 2:52 PM, Srinath Perera <[email protected]> wrote: >> >>> adding archtecture@ >>> >>> What tool did you used to train the regression? Is it WSO2 ML. Can you >>> share details about the process? >>> >>> --Srinath >>> >>> On Mon, Jul 25, 2016 at 2:04 PM, Sanjaya De Silva <[email protected]> >>> wrote: >>> >>>> Hi all, >>>> >>>> Following are the files that I used to train and test. >>>> >>>> On Mon, Jul 25, 2016 at 1:59 PM, Nihla Akram <[email protected]> wrote: >>>> >>>>> Hello All, >>>>> >>>>> >>>>> The following are few attachments which was used to train and test the >>>>> ML values obtained for clearing price. Please note that the predicted >>>>> values weren't accurate. >>>>> *trainerData.csv* is the file used to train the model. >>>>> *resultData.csv* is the result file produced for predictions on* >>>>> testData.csv* file. >>>>> >>>>> >>>>> The configurations of the Model were as follows. >>>>> Algorithm : Linear Regression >>>>> Response variable : clearingprice >>>>> Train data fraction : 0.7 >>>>> >>>>> >>>>> >>>>> Thanks, >>>>> Nihla >>>>> >>>>> >>>>> -- >>>>> *Nihla Akram* >>>>> Software Engineering Intern >>>>> >>>>> +94 72 667 9482 <%2B94%2072%6679482> >>>>> >>>>> >>>> >>>> >>>> -- >>>> Thank you >>>> Best Regards >>>> >>>> Sanjaya De Silva >>>> Trainee Software Engineer >>>> WSO2 >>>> +94774181056 >>>> >>> >>> >>> >>> -- >>> ============================ >>> Srinath Perera, Ph.D. >>> http://people.apache.org/~hemapani/ >>> http://srinathsview.blogspot.com/ >>> >> >> >> >> -- >> *Nihla Akram* >> Software Engineering Intern >> >> +94 72 667 9482 <%2B94%2072%6679482> >> >> >> _______________________________________________ >> Architecture mailing list >> [email protected] >> https://mail.wso2.org/cgi-bin/mailman/listinfo/architecture >> >> > > > -- > > Thanks & regards, > Nirmal > > Team Lead - WSO2 Machine Learner > Associate Technical Lead - Data Technologies Team, WSO2 Inc. > Mobile: +94715779733 > Blog: http://nirmalfdo.blogspot.com/ > > > > -- Thanks & regards, Nirmal Team Lead - WSO2 Machine Learner Associate Technical Lead - Data Technologies Team, WSO2 Inc. Mobile: +94715779733 Blog: http://nirmalfdo.blogspot.com/
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