https://github.com/radlfabs/flexcv-earth

Python Wrapper Class for R::Earth Regression Splines using rpy2
https://github.com/radlfabs/flexcv-earth

machine-learning-algorithms prediciton regression

Last synced: 26 days ago
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Python Wrapper Class for R::Earth Regression Splines using rpy2

• Host: GitHub
• URL: https://github.com/radlfabs/flexcv-earth
• Owner: radlfabs
• License: mit
• Created: 2023-11-15T16:16:43.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2023-11-16T18:08:24.000Z (about 1 year ago)
• Last Synced: 2024-10-28T14:37:41.194Z (2 months ago)
• Topics: machine-learning-algorithms, prediciton, regression
• Language: Python
• Homepage: https://radlfabs.github.io/flexcv-earth/
• Size: 990 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# flexcv-earth

This is a additional package for the python package [flexcv](https://github.com/radlfabs/flecv).

`flexcv-earth` provides a wrapper class to use Earth model regression in python without the need to install `pyearth`.

Instead, `flexcv-earth` uses the `rpy2` package to call the `earth` function from the `earth` package in R.

## Installation

Make sure to have Python 3.10 or 3.11 installed. Also, you will need to install R

```

pip install flexcv_earth @ git+https://github.com/radlfabs/flexcv-earth

```

#### Additional dependencies of `rpy2`

The model class for the `EarthRegressor` is actually wrapping around `rpy2` code and is using embedded `R` under the hood. 

Therefore, you should have a recent `R` version installed and run our `install_rpackages.py` script. 

From the command line change your directory to your `flexcv-earth` installation directory. 

This can be your folder that you created with `venv`. Run our python script that installs the remaining R dependencies.

```bash

cd path/to/flexcv-earth/

python -m install_rpackages

```

Now you have installed everything you need to use the `EarthRegressor`with flexcv-earth.