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Everything about Automatic basis function construction
Concept in machine learning
In machine learning, automatic basis function construction, also known as basis discovery, is a technique that finds a set of general-purpose (task-independent) basis functions to simplify complex data into a smaller, manageable form while accurately capturing the value function. Unlike methods relying on expert-designed functions, this approach works without prior knowledge of the specific problem area (domain), making it effective in situations where creating tailored basis functions is challenging or impractical. Wikipedia →
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- Read the overview: Automatic basis function constructionA 5-minute orientation
- Pick up a classic book: Intelligence BulletinThe most-reprinted book on the subject
- Go sideways: SuperspaceA closely related topic
- Go sideways: Wrapped distributionA closely related topic
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📚 Books worth reading
Intelligence BulletinUnited States. War Department. Military Intelligence Service · 1942
Neural Information ProcessingTingwen Huang · 2012
Cartesian meditationsEdmund Husserl, Dorion Cairns · 1960
Information Processing in Medical ImagingJames C. Gee · 2013
Principles of gene manipulation and genomicsS. B. Primrose · 2006
Pragmatism and the problem of the ideaJohn Thomas Driscoll · 1915
Advances in Multimedia Information Processing – PCM 2012Weisi Lin · 2012
Waldara AnswersWilliam Swygard · 1974
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