supervised learning
A machine learning paradigm where a model is trained on labeled data. The term is used in computing and AI contexts.
In supervised learning, the model is trained using pairs of inputs and correct labels.
Supervised learning is suitable for this classification problem.
Unsupervised learning, where the model is trained on data without explicit labels, in contrast to 教師あり学習.
Semi-supervised learning, which uses a small amount of labeled data together with a large amount of unlabeled data.
Compound of 教師 (teacher) + あり (existence) + 学習 (learning), literally 'learning with a teacher', referring to the presence of labeled guidance during training.