An extensible framework for automatically generating a large amount of 2D features (in the observations by features format) relevant to causality detection.
- Understandable code
- Customizability
- Reproducibility
- Python 2.7
- numpy
- scipy
- pandas
- scikit-learn
- boomlet (http://github.com/diogo149/boomlet)
- progress
More features could be added, but based on testing, features perform better than expected.
Copy the settings template, make changes to it, and pass the pairs of variables and the new settings file to the autocause.core.featurize function.
- data for SUP1 and SUP2 have been split (too large for github) with the following command: split --bytes=90m CEdata_train_pairs.csv CEdata_train_pairs.csv
- recombine the split files into the original with the command: cat CEdata_train_pairs.csv* > CEdata_train_pairs.csv
If you're interested in using this or new features, send me an email at diogo149@gmail.com and we can talk about it.