最小二乘支持向量机，程序粘到command window里，设定 2 两个参数，可以更改，以达到最优化-igam=0.001 isig2=0.001 [gam,sig2]=tunelssvm({X,Y, f ,igam,isig2, RBF_kernel },... [0.001 0.001 10000 10000], gridsearch ,{}, leaveoneout_lssvm ) type= function approximation kernel= RBF_

等渗的插图对生成的数据回归。等张回归发现引入近似函数的同时最小化均方误差的训练数据。-An illustration of the isotonic regression on generated data. The isotonic regression finds a non-decreasing approximation of a function while minimizing the mean squared error on the training data.