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Property | Description |
---|---|
<model storage-location> | ML model storage location is either the file system or Registry. If the model is stored in the Registry, storage-location should have the prefix |
<percentile value> | Percentile The percentile value for the prediction. This should be a double value between 0-100. 95.0 is default. It is required to specify a percentile value when the ML model uses an algorithm of the Anomaly Detection type. This property is optional for other algorithm types. For more information about algorithms of the Anomaly Detection type, see Machine Learner Algorithms. |
<name> | Name of the feature according to the generated model. |
<expression> | The XPath or JSONPath expression to extract the feature value from the payload. |
<predictionOutput property> | The message context property name, to which you need to set the prediction output value. |
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- Download WSO2 ESB version 4.9.x or later.
- Start the WSO2 ESB server as follows.
- on Linux, run
<ESB_HOME>/bin/wso2server.sh
on MS Windows, run
<ESB_HOME>/bin/wso2server.bat
- on Linux, run
- Log in to the WSO2 ESB management console using
admin/admin
credentials, and click Configure. - Click Features, and then click Repository Management.
- Click Add Repository, and enter the details as shown below to add the P2 repository.
- Click Add.
- Click Available Features tab, and select the repository added in the previous step.
Deselect the Group features by category check box.
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 cannot see this feature, retry with one of the following suggestions:
- Add a more recent P2 repository. The repository you added could be deprecated.
- Check for the feature in the Installed Features tab.
Once the features are selected, click Install to proceed with the installation.
Click Next, select I accept the terms of the license agreement option, and then click Next.
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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- 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 Design View link of the WSDL based proxy service you added above.
- Click Next in the Step 1 of 3 - Basic Settings screen to proceed to step 2.
- In the Step 2 of 3 - In Sequence and Endpoint Options screen, Select Define Inline, and then click the Create link as shown below.
- In the Design in Sequence screen, click the Add Child option which is next to the Root element.
- Select Core, and then select Log from the drop down menu as shown below.
- 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'))
Click Update.
- Click on the Log element, and then click the Add Sibling option which is next to it.
- Select Agent and then select Predict from the drop down menu as shown below.
Enter the path to generated model that you want to use in predictions for Model Storage Location as shown in the example below.
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.Click Load Model. It loads thefeatures list of the model as shown below.
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 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.
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.- Click Update.
- Click on the Predict element, and then click the Add Sibling option which is next to it.
- Select Core and then select Log from the drop down menu as shown below.
- 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'))
Click Update.
- Click on the Log element, and then click the Add Sibling option which is next to it.
- Select Core and then select Drop from the drop down menu as shown below.
- Click Save & Close.
Click Next in the Step 2 of 3 - In Sequence and Endpoint Options screen.
Click Finish in the Step 3 of 3 0 Out Sequence and Fault Sequence Options screen.
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