Deploying Java models for Decision Optimization
You can deploy Decision Optimization Java models in Watson Machine Learning by using the Watson Machine Learning REST API.
With the Java worker API, you can create optimization models with OPL, CPLEX, and CP Optimizer Java APIs. Therefore, you can easily create your models locally, package them and deploy them on Watson Machine Learning by using the boilerplate that is provided in the public Java worker GitHub.
Java worker GitHub contains a boilerplate with everything that you need to run,
deploy, and verify your Java models in Watson Machine Learning,
including an example. You can use the code in this repository to package your Decision
Optimization Java model in a
.jar file that can be used as a Watson Machine Learning model. For more information about Java
worker parameters, see the Java documentation.
You can build your Decision Optimization models in Java or you can use Java worker to package CPLEX, CPO, and OPL models.