Organisation(s):
Dar es Salaam Institute of Technology - Tanzania
TERNET - Tanzania
Brunel University London – United Kingdom
Department of Physics and Astronomy – University of Catania – Italy
Champion(s):
Other Member(s):
Dr. Joseph W. Matiko
Dr. Simon TAYLOR
Dr. Anastasia ANAGNOSTOU
Eng. Mario TORRISI
Prof. Roberto BARBERA
Use Case Description
Integration of WEKA in a Science Gateway
Integration of the Waikato Environment for Knowledge Analysis (WEKA) collection of machine learning algorithms for data mining tasks in a Science Gateway. WEKA will be trained with the Wisconsin Breast Cancer datasets from the UCI Machine Learning Repository to help doctors in Tanzania to distinguish breast cancer from benign samples.
e-Infrastructure Services Exploited
The main outcome of the use case is a JSR 168/286 standard-based “portlet”, which will be integrated in the Africa Grid Science Gateway.
For running WEKA, the Africa Grid Science Gateway is connected to a FutureGateway API Server - developed in the context of the INDIGO-DataCloud project - which seamlessly executes jobs on local, Grid and Cloud resources belonging to the Africa & Arabia Regional Operation Centre.