Offline learning
Encyclopedia
In machine learning
, systems which employ offline learning do not change their approximation of the target function once the initial training phase has been absolved. These systems are also typically examples of eager learning
.
Machine learning
Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases...
, systems which employ offline learning do not change their approximation of the target function once the initial training phase has been absolved. These systems are also typically examples of eager learning
Eager learning
In artificial intelligence, eager learning is a learning method in which the system tries to construct a general, input independent target function during training of the system, as opposed to lazy learning, where generalization beyond the training data is delayed until a query is made to the...
.
See also
- online learningOnline machine learningIn machine learning, online learning is a model of induction that learns one instance at atime. The goal in online learning is to predict labels for instances.For example, the instances could describe the current conditions of...
, the opposite model - online and offline algorithmsOnline algorithmIn computer science, an online algorithm is one that can process its input piece-by-piece in a serial fashion, i.e., in the order that the input is fed to the algorithm, without having the entire input available from the start. In contrast, an offline algorithm is given the whole problem data from...