基于Scikit-learn的支持向量回归分析

Support Vector Regression Analysis Based on Scikit-learn

本文使用python的机器学习库——Scikit-learn实现支持向量回归(SVR)。在人工数据集上,RBF核的SVR比线性核和多项式核的SVR表现出了较好的数据拟合能力。本文在经典的UCI数据集上分别使用线性核、多项式核和RBF核的SVR进行回归分析,并对三种模型进行了分析比较。

In this paper,We use python’s machine learning library——Scikit-learn to do support vector regression(SVR).In the artificial data set,the SVR of RBF kernel shows better data fitting ability than that of linear kernel and polynomial kernel.In this paper,the SVR of linear kernel,polynomial kernel and RBF kernel are used for regression analysis on classical UCI data sets.The three models are analyzed and compared.