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MARS算法理论和Python代码实现:用分段回归解决非线性时间序列预测问题
多元自适应回归样条(Multivariate Adaptive Regression Splines, MARS)是Jerome Friedman于1991年提出的一种非参数回归技术。该方法专门用于建模预测变量集合与目标变量之间的复杂非线性关系,无需预先确定具体的函数形式。本文将深入探讨MARS算法的核心原理,并详细阐述其在时间序列预测任务中的应用策略与技术实现。
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