A notebook covering the following topics
- Imbalanced data
- Resampling
- Data cleaning
- Data manipulation
- Feature selection
- Imbalanced classification scoring
- Hyper parameter tuning
- Decision trees, random forests, gradient boosted decision trees
Libraries used:
- pandas
- numpy
- seaborn for visualisations
- sci* kit learn
- imblearn for resampling imbalanced data
To view notebook click above or if you'd like to clone this notebook use the following
git clone https://github.com/jcarpenter12/Imbalanced* Classification.git