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 evaluate resulting models and standards,
- to formulate the appropriate data utilization mechanisms for 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
- Mining complex data: text, images, web data, etc.
- Reinforced Learning
- Deep Learning
- Evaluation metrics
- Problems in Knowledge Discovery