FAME3R: a re-implementation of the FAME3 model
Project description
FAME3R: a re-implementation of the FAME3 model.
Installation
- Create a conda environment with the required python version:
conda create --name fame3r-env python=3.10
- Activate the environment:
conda activate fame3r-env
- Install package:
pip install fame3r
Usage
Determining the optimal hyperparameters via k-fold cross-validation
fame3r-cv-hp-search -i INPUT_FILE -o OUTPUT_FOLDER -r RADIUS[OPTIONAL, DEFAULT=5] -n NUMFOLDS[OPTIONAL, DEFAULT=10]
Training a model
fame3r-train -i INPUT_FILE -o OUTPUT_FOLDER -r RADIUS[OPTIONAL, DEFAULT=5]
Applying a trained model on some (labeled) test data
fame3r-test -i INPUT_FILE -m MODEL_FOLDER -o OUTPUT_FOLDER -r RADIUS[OPTIONAL, DEFAULT=5] -t THRESHOLD[OPTIONAL, DEFAULT=0.2]
Computing the SoMs of some unlabeled data
fame3r-infer -i INPUT_FILE -m MODEL_FOLDER -o OUTPUT_FOLDER -r RADIUS[OPTIONAL, DEFAULT=5] -t THRESHOLD[OPTIONAL, DEFAULT=0.2]
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