Thanks everyone. So, we decided to have following improvements;
1. /s/ml/machineLearner 2. Instead of specifying storage-location, we should get the model-name from the user. 3. feature elements should be wrapped from a features element. 4. prediction element currently replaces an existing element in the incoming message, we can support the append as well. On Tue, Mar 24, 2015 at 11:56 PM, Chanaka Fernando <[email protected]> wrote: > Hi Manorama, > > I guess that the names are not finalized yet. The name "ml" does not make > much impression on the users. Please give a valid name like > "MachineLearner" and that would make life easier for ESB developers. All > our mediators has self explanatory names. > > Thanks, > Chanaka > > On Tue, Mar 24, 2015 at 4:09 PM, Supun Sethunga <[email protected]> wrote: > >> Hi Maninda, >> >> With the initial release of ML, the model would not update on the fly. If >> we need to update the model, it has to be done in ML by training a model >> with the same configurations, but with the new data. In future releases we >> will be looking at this for possible improvements. >> >> Here the term "domain" refers to the definition of the data which use to >> train the model. In the case you mentioned, If the model was trained using >> the data collected from all incoming requests; then domain is "all sales". >> and can be used to handle all incoming requests. But if the model was >> trained using the data collected from the incoming requests of, say >> Seller_A, then it cannot be used to predict/handle incoming requests of all >> sellers, which is a different domain. >> When we say "domain", it also includes the Schema (set of >> features/variables) of the dataset on which the prediction is going to be >> done. Handling multiple schema is tricky. If the data from a different >> domain doesn't contain some of the features (variables in the dataset) used >> to train the model, then that model cannot be used to predict on that >> particular data. So we have to work with this limitation, hence all the >> data has to be on the same domain (i.e. should have the same schema). >> >> Regards, >> Supun >> >> On Tue, Mar 24, 2015 at 3:10 PM, Maninda Edirisooriya <[email protected]> >> wrote: >> >>> Does this update the model time to time or use the same modal throughout >>> the ESB up time? It is better if we can update the model while the ESB is >>> up and running. >>> There may be some use cases related to multiple domains right? So I >>> think would be more generic and useful if we can apply the mediator not >>> based on the domain but with a custom argument expression. For example if >>> the target service is SalesService and the operation is getTotalSalesCount >>> we want to use the modal to analyze all incoming requests from all domains. >>> WDYT? >>> >>> Thanks. >>> >>> >>> *Maninda Edirisooriya* >>> Senior Software Engineer >>> >>> *WSO2, Inc.*lean.enterprise.middleware. >>> >>> *Blog* : http://maninda.blogspot.com/ >>> *E-mail* : [email protected] >>> *Skype* : @manindae >>> *Twitter* : @maninda >>> >>> On Tue, Mar 24, 2015 at 12:00 PM, Manorama Perera <[email protected]> >>> wrote: >>> >>>> Hi, >>>> >>>> ESB mediator for WSO2 ML enables making use of the models generated by >>>> WSO2 Machine Leaner, to predict values in message mediation in ESB. >>>> >>>> - Machine Learner feature needs to be installed in ESB prior to >>>> configure the ML mediator. >>>> - Mediator will extract the data from the incoming messages and >>>> send to the ML model as features. >>>> - The mediator use the Machine Learner features to predict the >>>> output value for every message passing through the mediator. >>>> >>>> *Proposed Mediator Configuration* >>>> >>>> <ml> >>>> <model storage-location="string"/> >>>> <feature name="string" expression="xpath"/>+ >>>> <prediction expression="xpath"/> >>>> </ml> >>>> >>>> *model* >>>> storage-location : Storage location of the generated model. >>>> >>>> *feature* >>>> name : Feature name according to the generated model. >>>> expression : XPath expression used to determine the feature value. >>>> >>>> *prediction* >>>> expression : XPath expression to determine the location to insert the >>>> predicted value. >>>> >>>> The generated models can be applied to predict only the data coming >>>> from the same domain, as the data used to train the model. So the mediator >>>> should be configured only to mediate messages which carry data coming from >>>> the same domain, as the data used to train the model. >>>> >>>> Any suggestion are appreciated. >>>> >>>> Thanks. >>>> >>>> -- >>>> Manorama Perera >>>> Software Engineer >>>> WSO2, Inc.; http://wso2.com/ >>>> Mobile : +94716436216 >>>> >>>> _______________________________________________ >>>> Architecture mailing list >>>> [email protected] >>>> https://mail.wso2.org/cgi-bin/mailman/listinfo/architecture >>>> >>>> >>> >>> _______________________________________________ >>> Architecture mailing list >>> [email protected] >>> https://mail.wso2.org/cgi-bin/mailman/listinfo/architecture >>> >>> >> >> >> -- >> *Supun Sethunga* >> Software Engineer >> WSO2, Inc. >> http://wso2.com/ >> lean | enterprise | middleware >> Mobile : +94 716546324 >> >> _______________________________________________ >> Architecture mailing list >> [email protected] >> https://mail.wso2.org/cgi-bin/mailman/listinfo/architecture >> >> > > > -- > -- > Chanaka Fernando > Technical Lead > WSO2, Inc.; http://wso2.com > lean.enterprise.middleware > > mobile: +94 773337238 > Blog : http://soatutorials.blogspot.com > LinkedIn:http://www.linkedin.com/pub/chanaka-fernando/19/a20/5b0 > Twitter:https://twitter.com/chanakaudaya > Wordpress:http://chanakaudaya.wordpress.com > > > > > _______________________________________________ > Architecture mailing list > [email protected] > https://mail.wso2.org/cgi-bin/mailman/listinfo/architecture > > -- Thanks & regards, Nirmal Senior Software Engineer- Platform Technologies Team, WSO2 Inc. Mobile: +94715779733 Blog: http://nirmalfdo.blogspot.com/
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