本文探讨了在机器学习中使用正则化技术来控制过拟合现象的方法，通过在误差函数中加入惩罚项，限制系数的大小，从而达到防止模型过度拟合的目的。介绍了最简单的惩罚项形式及其如何影响修改后的误差函数。
One technique that is often used to control the over-fitting phenomenon in such cases is that of regularization, which involves adding a penalty term to the error function (1.2) in order to discourage the coefficients from reaching large values. The simplest such penalty term takes the form of a sum of squares of all of the coefficients, leading to a modified error function of the form:
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