AI 中文总结
介绍用于软聚类的开源Python框架SCPP，它建立规范接口统一多种软聚类方法，集成40种算法及综合基准测试，提供文档、示例等，实现可重复实验与新算法扩展。
AI 中文摘要
本文介绍了SCPP（软聚类Python包），一个用于软聚类的开源Python框架。SCPP建立了一个规范的、与scikit-learn兼容的估计器接口，标准化了跨异构软聚类方法的模型训练、预测、成员表示、评估和基准测试。该框架目前集成了40种代表性算法，以及由数据集、聚类质量指标和标准化运行时、内存和可扩展性评估组成的综合基准测试。SCPP还提供了广泛的文档、实际示例、自动测试以及与科学Python生态系统的无缝集成，实现了可重复实验和新算法的直接扩展。源代码可通过此https URL公开获取。
英文摘要
In this paper, we present SCPP (Soft Clustering Python Package), an open-source Python framework for soft clustering. SCPP establishes a canonical, scikit-learn-compatible estimator interface that standardizes model training, prediction, membership representation, evaluation, and benchmarking across heterogeneous soft clustering methods, including fuzzy, probabilistic, graph-based, matrix factorization, and deep learning methods. The framework currently integrates 40 representative algorithms together with a comprehensive benchmarking comprising datasets, clustering quality metrics, and standardized runtime, memory, and scalability evaluation. SCPP further provides extensive documentation, practical examples, automated testing, and seamless integration with the scientific Python ecosystem, enabling reproducible experimentation and straightforward extension with new algorithms. The source code is publicly available at https://github.com/soft-clustering/soft-clustering.
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