机器学习的 label 和 feature 的概念

摘录 reddit 连接上一段话
The label is the name of some category. If you're building a machine learning system to distinguish fruits coming down a conveyor belt, labels for training samples might be "apple", " orange", "banana". The features are any kind of information you can extract about each sample. In our example, you might have one feature for colour, another for weight, another for length, and another for width. Maybe you would have some measure of concavity or linearity or ball-ness.

机器学习中有label 和 feature概念, 对于英文好的同窗很容易理解。但可能较差的同窗一开始不理解(我也是)。上面的英文对这俩概念作了解释，label是分类，你要预测的东西，而feature则是特征(好比你经过一些特征黄色，圆，得出是月亮)。若是你训练出feature和label的关系，以后你能够经过feature得出label。