Knowledge Discovery end Decision Support Systems
Module ID
E705
Semester
7
Hours/Week - ECTS
4 – 5
Fotios Kokkoras
Assistant Professor
Learning Outcomes
Upon successful completion of the course, the student will be able:
- to understand the complex and iterative process of knowledge discovery from data,
- to list the types of knowledge that are generated and the algorithms that perform the mining,
- to understand and apply machine learning algorithms to data,
- to perceive under/over-fitting phenomena and deal with them,
- to apply the above in the context of decision support.
Indicative Module Content
- Knowledge discovery from data – the steps.
- Predictive Models and Informative Patterns as Tools for Decision Making.
- Knowledge discovery as an application of machine learning algorithms.
- Supervised learning:
- classification,
- regression.
- Unsupervised learning
- clustering,
- association rules.
- Neural Networks.
- Deep Learning, Deep Neural Networks.
- Evaluation metrics.
- Problems in Knowledge Discovery.