機器學習的 label 和 feature 的概念

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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.

機器學習中有label 和 feature概念, 對於英文好的同窗很容易理解。但可能較差的同窗一開始不理解(我也是)。上面的英文對這倆概念作了解釋，label是分類，你要預測的東西，而feature則是特徵(好比你經過一些特徵黃色，圓，得出是月亮)。若是你訓練出feature和label的關係，以後你能夠經過feature得出label。