Machine learning is a very central topic in Artificial Intelligence and even
computer science in general. Nowadays, its use in Big Data problems is quite
well known. However, while the big data, and machine learning problems in
general, are quite varied and in needing of different kinds of solutions, there are
as well many different methods in machine learning that can be used. In this
work, we propose an application that might help deciding on which machine
learning methods a user needs for a specified problem.
The application is an Intelligent Decision Support System for Machine
Learning Algorithm Recommendation for which we present the design, which
is centered around the combined use of the Case-Based Reasoning and RuleBased
Reasoning, for the recommending process, while also trying to make
the system easy to use and manage. We present a prototype of such a system,
and the implementation details of the two recommender algorithms. The
preliminary testing of the prototype shows it to be a promising tool
