https://github.com/philips-labs/pairwise-regression
https://github.com/philips-labs/pairwise-regression
Last synced: about 17 hours ago
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- Host: GitHub
- URL: https://github.com/philips-labs/pairwise-regression
- Owner: philips-labs
- License: other
- Created: 2022-02-11T14:38:48.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2022-03-29T15:22:11.000Z (over 3 years ago)
- Last Synced: 2025-06-08T21:02:15.915Z (4 months ago)
- Language: Jupyter Notebook
- Size: 805 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 2
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Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
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README
# pairwise-regression
This is a regression model for predicting a target value of interested based on nonlinear interactions between input features and a key variable. The key variable is a special input feature that is particularly critical for the target value of interest.
For instance, when predicting a child's weight as a target value of interest, the key predictor may be the child's age.
The module allows you to input a design matrix of multiple input features, designate a key variable among the features, and then fit a regression model learning the relationship and nonlinear interactions between feature and key variable.
For full model description, see paper [here](up date when link is out).
# Usage
A usage example with sample data is given [here](https://github.com/philips-internal/pairwise-regression/tree/main/example) for reference.
# Requirements
See [here](https://github.com/philips-internal/pairwise-regression/blob/main/requirements.txt) for package requirements.
# Contributing
We appreciate any contributions in the form of ideas, feature requests, bug reports, bug fixes, documentation improvements, code reformatting, and code submissions. You can contact the [maintainers](https://github.com/philips-internal/pairwise-regression/blob/main/MAINTAINERS.md). Please see the [Contributing guide](https://github.com/philips-internal/pairwise-regression/blob/main/CONTRIBUTING.md).