Metadata-Version: 2.1
Name: simpleppt
Version: 1.0
Summary: Python implementation of SimplePPT algorithm, with GPU acceleration
Home-page: https://github.com/LouisFaure/SimplePPT
Author: Louis Faure
Author-email: 
License: UNKNOWN
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        # SimplePPT
        Python implementation of [SimplePPT algorithm](https://doi.org/10.1137/1.9781611974010.89), with GPU acceleration.
        
        Please cite the following paper if you use it:
        ```
        Mao et al. (2015), SimplePPT: A simple principal tree algorithm, SIAM International Conference on Data Mining.
        ```
        
        Installation
        ------------
        
        ```bash
        pip install -U simpleppt
        ```
        
        Usage
        -----
        
        ```python
        from sklearn.datasets import make_classification
        import simpleppt
        
        X1, Y1 = make_classification(n_features=2, n_redundant=0, n_informative=2,
                                     n_clusters_per_class=1, n_classes=3)
        
        ppt=simpleppt.ppt(X1,Nodes=30,seed=1,progress=False,lam=10)
        simpleppt.project_ppt(ppt,X1, c=Y1)
        ```
        
        ![result](./ppt.png)
        
        
        GPU dependencies (optional)
        ---------------------------
        
        If you have a nvidia GPU, simpleppt can leverage CUDA computations for speedup in tree inference. The latest version of rapids framework is required (at least 0.17) it is recommanded to create a new conda environment:
        
            conda create -n SimplePPT-gpu -c rapidsai -c nvidia -c conda-forge -c defaults \
                rapids=0.19 python=3.8 cudatoolkit=11.0 -y
            conda activate SimplePPT-gpu
            pip install simpleppt
        
Platform: UNKNOWN
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