支持向量机回归和支持向量机_详细解释支持向量机

Support Vector Machine(SVM) is a supervised machine learning algorithm that is usually used in solving binary classification problems. It can also be applied in multi-class classification problems and regression problems. This article represents the mathematics behind the binary-class linear Support Vector Machines. Understanding mathematics helps implement and tune the models in practice. Moreover, you can build your own support vector machine model from scratch, and compare it with the one from Scikit-Learn. For details, you can read this article along with another article of mine.

支持向量机(SVM)是一种监督型机器学习算法，通常用于解决二进制分类问题。 它也可以应用于多类分类问题和回归问题。 本文介绍了二元类线性支持向量机背后的数学原理。 了解数学有助于在实践中实现和调整模型。 此外，您可以从头开始构建自己的支持向量机模型，并将其与Sci