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<predict>
<model storage-location="string"/>
<percentile value="95.0"/>
<features>
<feature name="string" expression="XPath | JSONPath">+
</features>
<predictionOutput property="string"/>
</predict>

The properties of the above configuration are described below.

<predictionOutput property>

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1. Download WSO2 ESB version 4.9.x or later.
2. Start the WSO2 ESB server as follows.
   
   1. • on Linux, run <ESB_HOME>/bin/wso2server.sh

      • on MS Windows, run <ESB_HOME>/bin/wso2server.bat

3. Log in to the WSO2 ESB management console using admin/admin credentials, and click Configure.
4.  Click Features, and then click Repository Management.
5. Click Add Repository, and enter the details as shown below to add the P2 repository.
   
6. Click Add.
7. Click Available Features tab, and select the repository added in the previous step.

8. Deselect the Group features by category check box.

9. Click Find Features. It can take a while to list out all the available features in the feature repository. Once listed, select the following features. 

   • Machine Learner Core 
   • Machine Learner Commons 
   • Machine Learner Database Service 
   • Metrics Group
   • Predict Mediator Aggregate

   Tip
   If you can't cannot see this feature, retry with one of the following suggestions: Try adding Add a more recent P2 repository. The repository you added could be deprecated. Check for the feature in the Installed Features tab.

   Image RemovedImage Added

10. Once the features are selected, click  Install  to proceed with the installation. 

11. Click Next, select I accept the terms of the license agreement option, and then click Next.

12. Click Restart Now, and then click Yes in the message which pops up. Wait a few seconds until the sever restarts, and refresh the screen.

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1. Log in to the WSO2 ESB management console using admin/admin credentials.
2. Click Main, and then click Proxy Service.
3. Click Pass Throgh Proxy.
4. Enter the details as shown below.
   
   • Enter a name for Proxy Service Name (E.g. PredictMediatirTestProxy).
   • Enter  http://localhost:9000/services/SimpleStockQuoteService  for Target URL.

5.   Click  Create . You view the proxy service created as shown below.
   

   Tip

   Follow the steps below to view the source view of the proxy service configuration you added. Log in to the WSO2 ESB management console using admin/admin credentials. Click Main, and then click List in the Services menu. Click the corresponding Source View link of the WSDL based proxy service you added above. You view its configuration in the source view as follows. Code Block language xml <proxy xmlns="http://ws.apache.org/ns/synapse" name="PredictMediatirTestProxy" transports="https,http" statistics="disable" trace="disable" startOnLoad="true"> <target> <inSequence> <log level="custom"> <property name="before-predict-mediator" expression="fn:concat('ML Mediator Prediction : ',get-property('result'))"/> </log> <predict> <model storage-location="/Users/praneesha/Documents/Product_Packs/ML/wso2ml-1.0.0-SNAPSHOT/samples/ml-model-usage/src/main/resources/downloaded-ml-model"/> <features> <feature name="SI2" expression="$body/features/SI2"/> <feature name="PG2" expression="$body/features/PG2"/> <feature name="Age" expression="$body/features/Age"/> <feature name="DBP" expression="$body/features/DBP"/> <feature name="BMI" expression="$body/features/BMI"/> <feature name="DPF" expression="$body/features/DPF"/> <feature name="TSFT" expression="$body/features/TSFT"/> <feature name="NumPregnancies" expression="$body/features/NumPregnancies"/> </features> <predictionOutput property="result"/> </predict> <log level="custom"> <property name="after-predict-mediator" expression="fn:concat('ML Mediator Prediction : ',get-property('result'))"/> </log> <drop/> </inSequence> <outSequence> <send/> </outSequence> <endpoint> <address uri="http://localhost:9000/services/SimpleStockQuoteService"/> </endpoint> </target> <description/> </proxy>

    

Adding Log, Predict and Drop Mediators to the Sequence

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1. Log in to the WSO2 ESB management console using admin/admin credentials.
2. Click Main, and then click List in the Services menu.
3. Click the corresponding Design View link of the WSDL based proxy service you added above.
4. Click Next in the Step 1 of 3 - Basic Settings screen to proceed to step 2.
5. In the Step 2 of 3 - In Sequence and Endpoint Options screen, Select Define Inline, and then click the Create link as shown below.
   
6. In the Design in Sequence screen, click the Add Child option which is next to the Root element.
7. Select Core, and then select  Log  from the drop down menu as shown below.
   
8. Enter the following details in the Log Mediator section as shown below.
   

   • Select INFO for Log Category.

   • Select Custom for Log Level.

   • Click Add Property.

   • Enter before-predict-mediator for Property Name.

   • Select Expression from the Property Value drop down list.

   • Enter the following expression for Value/Expression: fn:concat('ML Mediator Prediction : ',get-property('result'))

9. Click Update.

10. Click on the Log element, and then click the Add Sibling option which is next to it.
11. Select Agent and then select Predict from the drop down menu as shown below.
    

12. Enter the path to generated model , which that you want to use in predictions for Model Storage Location as shown in the example below.

    You can give the folder path of the <ML_HOME>/samples/model-usage/src/main/resources/downloaded-ml-model sample model

    Tip
    Info
    The model should be downloaded and saved in the registry or any location in your machine. The Model Storage Location parameter specifies the location in which the model is saved.

13. Image Modified Click Load Model. It loads thefeatures list of the model as shown below.
    Image Modified
    

    Info
    The the model that you are using for predictions is using an algorithm of the Anomaly Detection algorithm type, the Predict mediator is displayed with the Percentile Value as shown in the example below. Expand title Click to view Predict mediator with Percentile Value Image Added

14. Enter the following XPath (or JSONPath) expressions in the Expression field for the displayed features list associated with the model, to extract the feature values from the mediating message.

    Feature name	XPath expression
    Age	$body/features/Age
    BMI	$body/features/BMI
    DBP	$body/features/DBP
    DPF	$body/features/DPF
    NumPregnancies	$body/features/NumPregnancies
    PG2	$body/features/PG2
    SI2	$body/features/SI2
    TSFT	$body/features/TSFT

    Tip
    If you are defining a namespace in the XPATH expression, click the corresponding Namespaces link of the features to add namespaces. Then, in the Namespace Editor, add any number of namespace prefixes and URL that you have used in the expression as shown below.

15. In the Prediction Output section, the message context property name (e.g. result), to which the prediction output value needs to be set as shown below.

16. Click Update.
17. Click on the Predict element, and then click the Add Sibling option which is next to it.
18. Select  Core  and then select  Log  from the drop down menu as shown below.
    
    
19. Enter the following details in the Log Mediator section as shown below.
    
    

    • Select INFO for Log Category.

    • Select Custom for Log Level.

    • Click Add Property.

    • Enter after-predict-mediator for Property Name.

    • Select Expression from the Property Value drop down list.

    • Enter the following expression for Value/Expression:  fn:concat('ML Mediator Prediction : ',get-property('result'))

20. Click Update.

21. Click on the Log element, and then click the Add Sibling option which is next to it.
22. Select  Core  and then select  Drop  from the drop down menu as shown below.
    
23. Click Save & Close.

24. Click Next in the Step 2 of 3 - In Sequence and Endpoint Options screen.

25. Click Finish in the Step 3 of 3 0 Out Sequence and Fault Sequence Options screen.

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