This is my MS thesis project conducted at Poznan University of Technology under the supervision of prof. Mikołaj Morzy It aims to extend the work described in Similarity Forest by Sathe and Aggarwal and provide ease to use, Scikit-Learn compatible implementation. It can be used in Scikit-Learn pipelines and (hyper)parameter search, it includes testing (API compliance) and more. I will include necessary documentation.
Below you can find neccessary steps to install the project package. It assumes that you have Anaconda (or Miniconda) installed. If you don't, follow the steps from the docs: https://docs.conda.io/projects/conda/en/latest/user-guide/install/
Make sure that conda it's up to date
conda update conda
Clone this repository
git clone https://github.com/sfczekalski/similarity_forest
Go to the project folder
cd similarity_forest
Create conda environment
conda env create --file environment.yml
Activate conda environment
conda activate similarity-forest
Install simforest package
pip install .