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This is my inaugural blog post following the completion of my personal website’s construction. After nearly four days of strenuous effort, I have successfully finished building my website, which is showcased here. Despite the abundance of tutorials available that guide users on utilizing GitHub Pages and Jekyll to construct a blog website, this ... Read More
Feb.17 MM algorithm: Majoritize and minimize Out Lier and l1 loss function: l1损失函数 = 对l2损失函数赋予权重,之后在进行对权重的迭代,为极端值的权重更小,从的减少极端值对参数估计的影响. l1损失函数的问题在于无法求导,因此最优化的时候没办法求。 此时找l1的损失函数的RSS对应的lossfunction值,然后找这个点上的l2曲线。 High Leverage Point: 考虑 估计的敏感性:即估计值对真实值变动的敏感性 $ y_hat / y_i $ 指的是 当真实值Y改变一点是,对整体的模型参数估计 以及 之后的Y_hat预测,都有巨大影响 敏感性 = H... Read More