Hours per week : 2
Credits : 4
Participants: Min: 3 Max: 12 Expected: 6
Type of course: Seminar (Bachelor/Master)
In this seminar we will discuss different variations of meta learning, also known as ensemble learning.
The main assumption of meta learning is, that if one simple learner produces quite well results, the combination of multiple ones produce way better results.
We will discuss different meta learning strategies, together with possible use cases.
Possible Topics are :
- Random Forests
- Dynamic Weighted Majority
- Stacked Generalization
Form of Exam
oral presentation (30 minutes) and written examination(8pages) at the end of semester