线性回归-批量梯度下降

void lir_BGD()
{
    //在x中添加一列1,对应w0
    std::vector> x={
        {1,1.1,1.5},
        {1,1.3,1.9},
        {1,1.5,2.3},
        {1,1.7,2.7},
        {1,1.9,3.1},
        {1,2.1,3.5},
        {1,2.3,3.9},
        {1,2.5,4.3},
        {1,2.7,4.7},
        {1,2.9,5.1}
    };

    std::vector y={
        2.5,
        3.2,
        3.9,
        4.6,
        5.3,
        6,
        6.7,
        7.4,
        8.1,
        8.8
    };

    //学习速率
    double alpha=0.01;
    std::vector w=std::vector(x[0].size(),0);
    //每个w的导数
    std::vector deri=std::vector(x[0].size(),0);

    int loop=1;
    while(loop++<10000) {
        for(auto &iter:deri) iter=0;

        for(int i=0;i

转载于:https://www.cnblogs.com/smallredness/p/10737559.html