Synonyms
Adaptive learning; Dynamic selection of bias; Learning to learn; Ranking learning methods; self-adaptive systems
Definition
Metalearning allows machine learning systems to benefit from their repetitive application. If a learning system fails to perform efficiently, one would expect the learning mechanism itself to adapt in case the same task is presented again. Metalearning differs from base-learning in the scope of the level of adaptation; whereas learning at the base-level is focused on accumulating experience on a specific task (e.g., credit rating, medical diagnosis, mine-rock discrimination, fraud detection, etc.), learning at the metalevel is concerned with accumulating experience on the performance of multiple applications of a learning system.
Briefly stated, the field of metalearning is focused on the relation between tasks or domains, and learning algorithms. Rather than starting afresh on each new task, metalearning facilitates evaluation and comparison of learning...
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Recommended Reading
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Brazdil, P., Vilalta, R., Giraud-Carrier, C., Soares, C. (2011). Metalearning. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30164-8_538
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DOI: https://doi.org/10.1007/978-0-387-30164-8_538
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-30768-8
Online ISBN: 978-0-387-30164-8
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