Case study in active learning

This case study uses another well-known publicly available dataset to demonstrate active learning techniques using open source Java libraries. As before, we begin with defining the business problem, what tools and frameworks are used, how the principles of machine learning are realized in the solution, and what the data analysis steps reveal. Next, we describe the experiments that were conducted, evaluate the performance of the various models, and provide an analysis of the results.

Tools and software

For the experiments in Active Learning, JCLAL was the tool used. JCLAL is a Java framework for Active Learning, supporting single-label and multi-label learning.

Note

JCLAL is open source and is distributed under the GNU general public license: https://sourceforge.net/p/jclal/git/ci/master/tree/.

Business problem

The abalone dataset, which is used in these experiments, contains data on various physical and anatomical characteristics of abalone—commonly known...