摘要:
本节主要是练习regularization项的使用原则。因为在机器学习的一些模型中,如果模型的参数太多,而训练样本又太少的话,这样训练出来的模型很容易产生过拟合现象。因此在模型的损失函数中,需要对模型的参数进行“惩罚”,这样的话这些参数就不会太大,而越小的参数说明模型越简单,越简单的模型则越不容易产... 阅读全文
摘要:
DataFor this exercise, suppose that a high school has a dataset representing 40 students who were admitted to college and 40 students who were not adm... 阅读全文