Roadmap Kernel Trick Polynomial Kernel Gaussian Kernel Comparison of Kernels Summary…

Roadmap Course Introduction Large-Margin Separating Hyperplane Standard Large-Margin Problem Support Vector Machine Reasons behind Large-Margin Hyperplane Summary…

Roadmap Kernel Ridge Regression Support Vector Regression Primal Support Vector Regression Dual Summary of Kernel Models Map of Linear Models Map of Kernel Models possible kernels: polynomial, Gaussian,..., your design (with Mercer’s condition), coup…

Roadmap Kernel Trick Polynomial Kernel Gaussian Kernel Comparison of Kernels Summary…

Roadmap Motivation and Primal Problem Dual Problem Messages behind Soft-Margin SVM Model Selection Summary…

Roadmap Motivation of Dual SVM Lagrange Dual SVM Solving Dual SVM Messages behind Dual SVM Summary…

Lecture 12 支持向量机 Support Vector Machines 12.1 优化目标 Optimization Objective 支持向量机(Support Vector Machine) 是一个更加强大的算法,广泛应用于工业界和学术界.与逻辑回归和神经网络相比, SVM在学习复杂的非线性方程时提供了一种更为清晰,更加强大的方式.我们通过回顾逻辑回归,一步步将其修改为SVM. 首先回顾一下逻辑回归: 其 cost function 公式如下(这里稍微有点变化,将负号移到了括号内…

SVM被许多人认为是最强大的“黑箱”学习算法,并通过提出一个巧妙选择的优化目标,今天最广泛使用的学习算法之一. Optimization Objective 根据Logistic Regression,有如下表述: 为了达到尽量好的分类效果,我们需要theta‘*x >> 0 or theta‘*x << 0,根据上面的函数图象,这时候的h(x)->1 or h(x)->0,可以看出这时我们的分类效果是最具说服力的. 根据逻辑回归的Cost Function我们可以得到…

Roadmap Course Introduction Large-Margin Separating Hyperplane Standard Large-Margin Problem Support Vector Machine Reasons behind Large-Margin Hyperplane Summary…

第一阶段技法: large margin (the relationship between large marin and regularization), hard-SVM,soft-SVM,dual problem(解对偶问题),kernel trick,kernel logistic regression, 主要思路是:(这里不区分线性与非线性,差别只是特征空间转换,X空间与Z空间的关系) 1. 从PLA出发,对于二维平面的二分类问题,PLA可能得出一堆能够正确分类的直线,但是哪一条直线…