Overview of GAM Changer
The GAM Changer is an innovative interactive visualization tool designed to assist domain experts and data scientists in easily and responsibly editing Generalized Additive Models (GAMs). This tool simplifies the complex process of modifying machine learning models by providing an intuitive visual interface, making it accessible even to those who might not have deep technical expertise in model building.
Key Features
One of the standout features of GAM Changer is its user-friendly interface, which offers an interactive experience for editing models. This empowers users to adjust and refine GAMs based on their specific needs or insights, making the models more aligned with human knowledge and values. Its features are designed to facilitate an easier understanding and manipulation of these models without compromising on the robustness and accuracy they provide.
How to Get Started
For those eager to experiment with GAM Changer, a live demo is available at their official website. Users can engage with the demo to understand the tool's capabilities and apply it to their own GAMs. The process involves uploading model weights and sample data, which can be generated using the EBM (Explainable Boosting Machine) framework along with the GAM Changer Python package.
Here's a quick guide to get started:
- Install the GAM Changer Python package using
pip install gamchanger. - Utilize the provided code snippets to import necessary functions, extract model data, and save them appropriately.
- Use this prepared data within the GAM Changer to visualize and edit.
Integration in Computational Notebooks
GAM Changer can be seamlessly integrated into computational notebooks, such as Jupyter Notebook, VSCode Notebook, or Google Colab. The tool provides a straightforward code snippet to install, initialize, and visualize the models directly within the notebooks. This integration ensures that data scientists can continue working within their preferred environments without needing to switch tools.
Saving and Loading Edited Models
Once the models have been edited, GAM Changer allows users to save the new versions along with their editing histories to a special file format (*.gamchanger). This functionality ensures that any changes made are not only retained but can also be shared or revisited later. Loading these edited models back into Python is straightforward, enabling a smooth workflow for continuous improvement and adaptation of GAMs.
Development and Contribution
For developers interested in contributing to GAM Changer, the project is hosted on GitHub. Developers can clone or download the repository, install necessary dependencies, and run the project locally to start developing. This open approach encourages collaboration, innovation, and improvements to the tool.
Acknowledgements
GAM Changer is a collaborative effort of several researchers and professionals across institutions such as Microsoft Research, NYU Langone Health, Georgia Tech, and the University of Washington. Special thanks go to individuals for their contributions in developing this tool and for their ongoing support within the project ecosystem.
Get in Touch
For questions or contributions to the project, the team encourages reaching out through GitHub or contacting the lead developers directly. This openness supports a community-driven approach to further develop and enhance the capabilities of GAM Changer.
In summary, GAM Changer is not just a tool but a step towards making machine learning models more interpretable and aligned with human values, thereby fostering a greater understanding and control over automated decision-making processes.