Welcome to ProbNet’s documentation!¶

ProbNet is a lightweight and extensible Python library that provides a unified implementation of Probabilistic Neural Network (PNN) and its key variant, the General Regression Neural Network (GRNN). It supports both classification and regression tasks, making it suitable for a wide range of supervised learning applications.

• Free software: GNU General Public License (GPL) V3 license

• Provided Estimators: PnnClassifier, GrnnRegressor

• Supported Kernel Functions: Gaussian, Laplace, Triangular, Epanechnikov…

• Supported Distance Metrics: Euclidean, Manhattan, Chebyshev, Minkowski, Cosine, …

• Supported performance metrics: >= 67 (47 regressions and 20 classifications)

• Documentation: https://probnet.readthedocs.io

• Python versions: >= 3.8.x

• Dependencies: numpy, scipy, scikit-learn, pandas, permetrics

Indices and tables¶

• Index

• Module Index

• Search Page