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https://github.com/advestis/rice

Rule Induction Covering Estimator
https://github.com/advestis/rice

Last synced: about 2 months ago
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Rule Induction Covering Estimator

Host: GitHub
URL: https://github.com/advestis/rice
Owner: Advestis
License: gpl-3.0
Created: 2020-05-12T12:32:17.000Z (over 4 years ago)
Default Branch: master
Last Pushed: 2022-03-31T09:04:55.000Z (almost 3 years ago)
Last Synced: 2023-03-07T00:14:48.791Z (almost 2 years ago)
Language: Python
Size: 162 KB
Stars: 1
Watchers: 3
Forks: 1
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

        [![doc](https://img.shields.io/badge/-Documentation-blue)](https://advestis.github.io/RICE)

[![License: GPL v3](https://img.shields.io/badge/License-GPL%20v3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)

#### Status

![push](https://github.com/Advestis/RICE/actions/workflows/push.yml/badge.svg)

![maintained](https://img.shields.io/badge/Maintained%3F-no-red.svg)

![issues](https://img.shields.io/github/issues/Advestis/RICE.svg)

![pr](https://img.shields.io/github/issues-pr/Advestis/RICE.svg)

#### Compatibilities

![ubuntu](https://img.shields.io/badge/Ubuntu-supported--tested-success)

![unix](https://img.shields.io/badge/Other%20Unix-supported--untested-yellow)

![python](https://img.shields.io/pypi/pyversions/RICE)

##### Contact

[![linkedin](https://img.shields.io/badge/LinkedIn-Advestis-blue)](https://www.linkedin.com/company/advestis/)

[![website](https://img.shields.io/badge/website-Advestis.com-blue)](https://www.advestis.com/)

[![mail](https://img.shields.io/badge/mail-maintainers-blue)](mailto:[email protected])

# RICE

Implementation of a rule based prediction algorithm called RICE (Rule Induction Covering Estimator). RICE is a deterministic and interpretable algorithm, for regression problem.

## Getting Started

These instructions will get you a copy of the project up and running on your

local machine for development and testing purposes. See deployment for notes

on how to deploy the project on a live system.

### Prerequisites

RICE is developed in Python version 3.5 or greater. It requires some usual packages

- NumPy (post 1.13.0)

- Scikit-Learn (post 0.19.0)

- Pandas (post 0.16.0)

- SciPy (post 1.0.0) 

- Matplotlib (post 2.0.2) 

- Seaborn (post 0.8.1)

See **requirements.txt**.

```

sudo pip install package_name

```

To install a specific version

```

sudo pip install package_name==version

```

### Installing

The latest version can be installed from the master branch using pip:

```

pip install git+git://github.com/VMargot/RICE.git

```

Another option is to clone the repository and install using ```python setup.py

install``` or ```python setup.py develop```.

## Usage

RIPE has been developed to be used as a regressor from the package scikit-learn.

### Training

```

from sklearn import datasets

iris = datasets.load_iris()

X, y = iris.data, iris.target

rice = RICE.Learning()

rice.fit(X, y)

```

### Predict

```

rice.predict(X)

```

### Score

```

rice.score(X,y)

```

### Inspect rules:

To have the Pandas DataFrame of the selected rules

```

rice.selected_rs.to_df()

```

Or, one can use

```

rice.make_selected_df()

```

To draw the distance between selected rules

```

rice.plot_dist()

```

To draw the count of occurrence of variables in the selected rules

```

rice.plot_counter_variables()

```

## Notes

This implementation is in progress. If you find a bug, or something witch could

be improve don't hesitate to contact me.

## Authors

* **Vincent Margot**

See also the list of [contributors](https://github.com/VMargot/RICE/contributors)

who participated in this project.

## License

This project is licensed under the GNU v3.0 - see the [LICENSE.md](LICENSE.md)

file for details