In the last decade the usage and study of data mining and machine learning algorithms have received an increasing attention from several and heterogeneous fields of research. Learning how and why a certain algorithm returns a particular result, and understanding which are the main problems connected to its execution is a hot topic in the education of data mining methods. In order to support data mining beginners, students, teachers, and researchers we introduce a novel didactic environment.
The Didactic Data Mining Environment (DDME) allows to execute a data mining algorithm on a dataset and to observe the algorithm behavior step by step to learn how and why a certain result is returned. DDME can be practically exploited by teachers and students for having a more interactive learning of data mining. Indeed, on top of the core didactic library, we designed a visual platform that allows online execution of experiments and the visualization of the algorithm steps. The visual platform abstracts the coding activity and makes available the execution of algorithms to non-technicians.
Please cite the following paper above if you use our code or refer to our didactic environment:
Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo "Learning Data Mining", DSAA 2018, Turin, Italy.
The content of these slides is mainly based on the book:
Pang-Ning Tan, Michael Steinbach, Anuj Karpatne, Vipin Kumar "Introduction to Data Mining", 2nd Edition
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