This repo contains all code for a machine learning project I completed while attending the Technical University of Vienna. This project focused on the applications of various regression techniques using different datasets as listed below.
- Linear regression
- Support vector regression
- Gradient boosted decision tree
- H2O AutoML
- Bike sharing (Kaggle)
- https://www.kaggle.com/c/184702-tu-ml-ws-18-bike-sharing#_=_
- large samples (train = 8690), small dimension (15)
- attribute characteristics: numeric
- Student performance (Kaggle)
- https://www.kaggle.com/c/184702-tu-ml-ws-18-student-performance
- small samples (train = 198), medium dimension (32)
- attribute characteristics: numeric, categorical
- Blog feedback
- https://archive.ics.uci.edu/ml/datasets/BlogFeedback
- very large samples (60021), large dimension (281)
- attribute characteristics: numeric
- Forest fires
- https://archive.ics.uci.edu/ml/datasets/Forest+Fires
- medium samples (513), small dimension (13)
- attribute characteristics: numeric