RESTful API Webservice to WEKA Machine Learning Algorithms. This webservice provides an OpenRiskNet compliant REST interface to machine learning algorithms from the WEKA Java Library. This application is developed by the Institute of Computer Science at the Johannes Gutenberg University Mainz. OpenRiskNet is funded by the European Commission GA 731075. WEKA is developed by the Machine Learning Group at the University of Waikato.
See Documentation, Issue Tracker and Code at GitHub.
This is an a swagger-enabled JAX-RS server. The API is in OpenAPI Specification Version 3.0.1 OpenAPI-Specification 3.0.1 The service uses the JAX-RS framework.
To run a simple local environment, please execute the following:
mvn clean package jetty:run
You can then view the full Rest API on Swagger-UI here:
http://0.0.0.0:8081
To connect the server to a mongodb database you can use a standard mongo docker image pulled from docker hub:
docker pull mongo
docker run -d mongo
POST an arff file to the WEKA BayesNet algorithm using curl:
curl -X POST -H "Content-Type: multipart/form-data" -H "Accept:text/x-arff" -F "file=@/yourpathtowekadata/weka-3-8-1/data/weather.nominal.arff;" -F "estimatorParams=0.5" -F "searchAlgorithm=local.K2" -F useADTree=0 -F "estimator=SimpleEstimator" -F searchParams='-P 1 -S BAYES' http://0.0.0.0:8081/algorithm/BayesNet
- Full example for a local or server hosted development environment.
- Docker Deployment: Build the Docker image with a Dockerfile.
- Running tests: Run Tests.
- OpenShift Deployment: Deployment in OpenShift.
- Commandline Examples with Curl: Curl Examples.
- Authentication: Keycloak Integration.
- Java Docs on gh-pages: JavaDocs.