Description
To make predictions using locally weighted linear regression, we need to keep the entire training set around. The term “non-parametric” roughly refers to the fact that the amount of stuff we need to keep in order to represent the hypothesis h grows linearly with the size of the training set.
为了对输入进行预测，我们预测过程中需要保存所有训练集。 在进行预测时，我们需要使用的数据与训练集的大小成正比。