生成模型与判别模型

首先摘抄一段Andrew的话，从思想上把握一下区别：

Algorithms that try to learn p(y|x) directly (such as logistic regression), or algorithms that try to learn mappings directly from the space of inputs X to the labels {0, 1}, (such as the perceptron algorithm) are called discriminative learning algorithms. Here, we’ll talk about algorithms that instead try to model p(x|y) (and p(y)). These algorithms are called generative learning algorithms. For instance, if y indicates whether an example is a dog (0) or an elephant (1), then p(x|y = 0) models the distribution of dogs’ features, and p(x|y = 1) models the distribution of elephants’ features.

—— Ng, A. “Lecture notes for machine learning.” (2010).
已经很声情并茂了….

“生成式方法（generative methods）是直接基于生成式模型的方法。此类方法假设所有数据都是由一个潜在的模型生成的”——周志华

再看一个知乎的回答：

最后再看一个新浪微博(from 刘成林_NLPR)

至此应该能把握好二者的关系了吧。