论文标题
PYTSK：TSK模糊系统的Python工具箱
PyTSK: A Python Toolbox for TSK Fuzzy Systems
论文作者
论文摘要
本文介绍了Pytsk，这是一种用于开发Takagi-Sugeno-Kang（TSK）模糊系统的Python工具箱。基于Scikit-Learn和Pytorch，PYTSK允许用户使用基于模糊的聚类或基于迷你批处理梯度下降（MBGD）算法优化TSK模糊系统。工具箱中实现了几种基于MBGD的最先进的优化算法，这可以改善TSK模糊系统的概括性能，尤其是对于大数据应用程序。 PYTSK也可以轻松扩展和定制，以用于更复杂的算法，例如修改TSK模糊系统的结构，开发更复杂的培训算法，并将TSK模糊系统与神经网络相结合。可以在https://github.com/yuqicui/pytsk上找到PYTSK的代码。
This paper presents PyTSK, a Python toolbox for developing Takagi-Sugeno-Kang (TSK) fuzzy systems. Based on scikit-learn and PyTorch, PyTSK allows users to optimize TSK fuzzy systems using fuzzy clustering or mini-batch gradient descent (MBGD) based algorithms. Several state-of-the-art MBGD-based optimization algorithms are implemented in the toolbox, which can improve the generalization performance of TSK fuzzy systems, especially for big data applications. PyTSK can also be easily extended and customized for more complicated algorithms, such as modifying the structure of TSK fuzzy systems, developing more sophisticated training algorithms, and combining TSK fuzzy systems with neural networks. The code of PyTSK can be found at https://github.com/YuqiCui/pytsk.
