机器学习的 label 和 feature 的概念
摘录 reddit 上一段话 The label is the name of some category. If youre 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, 对于英文好的同学很容易理解。但可能较差的同学一开始不理解(我也是)。上面的英文对这俩概念做了解释，label是分类，你要预测的东西，而feature则是特征(比如你通过一些特征黄色，圆，得出是月亮)。如果你训练出feature和label的关系，之后你可以通过feature得出label。
摘录 reddit 上一段话 The label is the name of some category. If youre 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, 对于英文好的同学很容易理解。但可能较差的同学一开始不理解(我也是)。上面的英文对这俩概念做了解释，label是分类，你要预测的东西，而feature则是特征(比如你通过一些特征黄色，圆，得出是月亮)。如果你训练出feature和label的关系，之后你可以通过feature得出label。
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