Translations:Transfer Learning/6/en

Formally, a domain $ \mathcal{D} = \{\mathcal{X}, P(X)\} $ consists of a feature space $ \mathcal{X} $ and a marginal distribution $ P(X) $. A task $ \mathcal{T} = \{\mathcal{Y}, f(\cdot)\} $ consists of a label space $ \mathcal{Y} $ and a predictive function $ f $. Transfer learning applies when the source and target differ in domain, task, or both.