Completed
Random oversampling with replacement
Class Central Classrooms beta
YouTube videos curated by Class Central.
Classroom Contents
The Curse of Class Imbalance and Conflicting Metrics with Machine Learning for Side-channel Evaluation
Automatically move to the next video in the Classroom when playback concludes
- 1 Intro
- 2 Big Picture
- 3 Labels
- 4 Why do we use HW?
- 5 Why do we care about imbalanced data?
- 6 What to do?
- 7 Random under sampling
- 8 Random oversampling with replacement
- 9 Experiments
- 10 Dataset 1
- 11 Dataset 2
- 12 Data sampling techniques
- 13 Further results
- 14 Evaluation metrics
- 15 SR/GE vs acc
- 16 Take away
