SimplePPT

A python implementation of SimplePPT algorithm, with GPU acceleration.

Installation

pip install -U simpleppt

Usage

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)

SP = simpleppt.ppt(X1,Nodes=30,seed=1,progress=False,lam=10)
simpleppt.project_ppt(SP, X1, c=Y1)

Citation

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.

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 -n SimplePPT-gpu -c rapidsai -c nvidia -c conda-forge -c defaults cuml=23.04 cugraph=23.04 python=3.8 cudatoolkit=11.8 -y
conda activate SimplePPT-gpu
pip install simpleppt