Learn in the textbookThe Framework of Machine Learning
DefinitionA feature (特徴量) is one of an object's properties, chosen as a clue for learning or prediction and expressed as a number.
ExplanationData as collected also contains information that does not help with the decision, so the properties that serve the goal are picked out, turned into numbers, and used as the input for learning. Which features you choose has a large effect on how accurate the predictions are. People used to design features by hand, but in deep learning (ディープラーニング), a method that learns through many stacked layers of a structure modeled on the brain's neural circuits, the computer finds for itself what to focus on as it learns.
AnalogyThink of someone pricing a used bicycle who ignores whether they like the color and looks at the distance it has been ridden and how worn the tires are. Only the points that decide the price get picked out as numbers.
Memory hookThe Japanese name ends in 量 ("quantity"), meaning something expressed as a number: a characteristic turned into a value.