ASReview Dory is an extension to the ASReview software, providing new models for classification and feature extraction. The extension is maintained by the ASReview LAB team.
You can install ASReview Dory via PyPI using the following command:
pip install asreview-dory
⚠️ XGBoost on MacOS If you are using macOS and plan to use XGBoost, you should first install OpenMP (brew install libomp
)
Feature Extractors:
GTR T5
LaBSE
MPNet
Multilingual E5
MXBAI
Classifiers:
AdaBoost
Neural Network - 2-Layer
Neural Network - Dynamic
Neural Network - Warm Start
XGBoost
Explore the performance of these models in our Simulation Gallery! Look for the 🐟 icon to spot the Dory models.
Once installed, the plugins will be available in the front-end of ASReview, as well as being accessible via the command-line interface.
You can check all available models using:
asreview algorithms
You can pre-load models to avoid downloading them during runtime by using the
cache
command. To cache
specific models, such as xgboost
and sbert
, run:
asreview dory cache nb xgboost sbert
To cache all available models at once, use:
asreview dory cache-all
This plugin is compatible with ASReview version 2 or later. Ensure that your ASReview installation is up-to-date to avoid compatibility issues.
The development of this plugin is done in parallel with the development of the ASReview software. We aim to maintain compatibility with the latest version of ASReview, but please report any issues you encounter.
We welcome contributions from the community. To contribute, please follow these steps:
- Fork the repository.
- Create a new branch for your feature or bug fix.
- Implement your changes.
- Commit your changes with a clear message.
- Push your changes to your fork.
- Open a pull request to the main repository.
Please ensure your code adheres to the existing style and includes relevant tests.
For any questions or further assistance, feel free to contact the ASReview Lab Developers.
Enjoy using ASReview Dory! We hope these new models enhance your systematic review processes.