Best-Worst Counting and Gaussian Process Preference Learning: A Detailed Comparison

Code for the experiments conducted in the context of the Deep Learning & Digital Humanities Seminar. For a detailed analysis of the results please take a look at this term paper.

Setup

Clone the repository:

git clone --recurse-submodules git@github.com:DrCracket/dldh-experiments.git

Install requirements:

pip install -r requirements.txt

Put the annotated poetry data in to the poems folder. The files are expected to be in unix-flavored csv format. Put the file with real poems in the real_poems folder. The file should contain all real poems separated with a newline.

Experiments

Train models and compute features:

python gppl.py && python crowdgppl.py

Run the experiments:

python main.py

Compute various statistics of the dataset:

python statistics.py