Hi Supun, In a general supervised ML work flow we have to perform feature normalization [1] (This stage is after the feature extraction stage). This step is very important to reduce the convergence time of the training algorithm.
How is the model selection going to happen in this approach? is it a user input or is it based on a modal selection algorithm? Since this doesn't cover the unsupervised learning isn't it good to name this as supervised ML workflow? [1] Feature scaling : http://en.wikipedia.org/wiki/Feature_scaling Regards, Anuruddha. On Tue, Aug 12, 2014 at 8:55 PM, Supun Sethunga <[email protected]> wrote: > [adding Lochana] > > > On Tue, Aug 12, 2014 at 6:05 PM, Supun Sethunga <[email protected]> wrote: > >> Hi Srinath, >> >> Attached is a proposed work-flow for the ML design came up by Lochana, >> Upul and me. >> >> Appreciate any comments. >> >> Regards, >> Supun >> >> -- >> *Supun Sethunga* >> Software Engineer >> WSO2, Inc. >> lean | enterprise | middleware >> Mobile : +94 716546324 >> > > > > -- > *Supun Sethunga* > Software Engineer > WSO2, Inc. > lean | enterprise | middleware > Mobile : +94 716546324 > > _______________________________________________ > Architecture mailing list > [email protected] > https://mail.wso2.org/cgi-bin/mailman/listinfo/architecture > > -- *Anuruddha Premalal* Software Eng. | WSO2 Inc. Mobile : +94710461070 Web site : www.regilandvalley.com
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