GenForge：一个基于语义保持特征划分的多种群遗传规划框架

IF 1.2 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Software Impacts Pub Date : 2026-04-01 Epub Date: 2026-01-28 DOI:10.1016/j.simpa.2026.100812

Mohammad Sadegh Khorshidi , Navid Yazdanjue , Hassan Gharoun , Mohammad Reza Nikoo , Fang Chen , Amir H. Gandomi

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引用次数: 0

摘要

GenForge是一个开源的Python包，用于通过多种群遗传编程进行可解释的符号建模。它将回归、分类和语义特征划分统一到一个进化学习框架中。通过集成多基因符号回归、集成进化和语义保留特征划分（SPFP）， GenForge支持高保真建模，同时保持透明度和简约性。该包为符号回归（grepregressor）、分类（gpclassifier）和特征分区（SPFPPartitioner）提供了模块，每个模块都有可重复的示例脚本和诊断可视化工具。GenForge在可解释的AI、符号学习和多视图集成建模方面支持可重复的研究和教育用途。

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GenForge: A Multi-population Genetic Programming framework with Semantic-Preserving Feature Partitioning for classification and regression tasks

GenForge is an open-source Python package for interpretable symbolic modeling through multi-population genetic programming. It unifies regression, classification, and semantic feature partitioning into a single evolutionary learning framework. By integrating multi-gene symbolic regression, ensemble evolution, and Semantic-Preserving Feature Partitioning (SPFP), GenForge enables high-fidelity modeling while maintaining transparency and parsimony. The package provides modules for symbolic regression (gpregressor), classification (gpclassifier), and feature partitioning (SPFPPartitioner), each with reproducible example scripts and diagnostic visualization tools. GenForge supports reproducible research and educational use in explainable AI, symbolic learning, and multi-view ensemble modeling.

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来源期刊

Software Impacts Software

CiteScore

2.70

自引率

9.50%

发文量

审稿时长

16 days