Inductive bias - Wikipedia
The inductive bias (also known as learning bias) of a learning algorithm is the set of assumptions that the learner uses to predict outputs of given inputs that it has not encountered.[1] Inductive bias is anything which makes the algorithm learn one pattern instead of another pattern (e.g. step-functions in decision trees instead of continuous function in a linear regression model). Learning is the process of apprehending useful knowledge by observing and interacting with the world.[2] It involves searching a space of solutions for one expected to provide a better explanation of the data or to achieve higher rewards. But in many cases, there are multiple solutions which are equally good.[3] An inductive bias allows a learning algorithm to prioritize one solution (or interpretation) over another, independent of the observed data.[4]
Inductive bias - Wikipedia Jump to content From Wikipedia, the free encyclopedia Assumptions for inference in machine learning This article needs more citations . Please help improve this article by adding citations to reliable sources . Unsourced material may be challenged and removed . Find sources: "Inductive bias" – news · newspapers · books · scholar · JSTOR ( December 2025 ) ( Learn how and when to remove this message ) The inductive bias (also known as learning bias ) of a learning algorithm is the set of assumptions that the learner uses to predict outputs of given inputs that it has n
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