About: Automatic basis function construction

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In machine learning, automatic basis function construction (or basis discovery) is the mathematical method of looking for a set of task-independent basis functions that map the state space to a lower-dimensional embedding, while still representing the value function accurately. Automatic basis construction is independent of prior knowledge of the domain, which allows it to perform well where expert-constructed basis functions are difficult or impossible to create.

Attributes	Values
rdf:type	software
rdfs:label	Automatic basis function construction (en)
rdfs:comment	In machine learning, automatic basis function construction (or basis discovery) is the mathematical method of looking for a set of task-independent basis functions that map the state space to a lower-dimensional embedding, while still representing the value function accurately. Automatic basis construction is independent of prior knowledge of the domain, which allows it to perform well where expert-constructed basis functions are difficult or impossible to create. (en)
sameAs	Automatic basis function construction Automatic basis function construction
dbp:wikiPageUsesTemplate	dbt:Citation_needed dbt:Reflist dbt:Technical
Subject	Dynamic programming Stochastic control Optimal decisions
Link from a Wikipage to an external page	http://www-all.cs.umass.edu/
gold:hypernym	Method
prov:wasDerivedFrom	http://en.wikipedia.org/wiki/Automatic_basis_function_construction?oldid=1071973701&ns=0
Wikipage page ID	34073749 (xsd:integer)
page length (characters) of wiki page	9655 (xsd:nonNegativeInteger)
Wikipage revision ID	1071973701 (xsd:integer)
Link from a Wikipage to another Wikipage	Machine learning Adjacency matrix Basis function Bellman equation State space Dynamic programming Domain (mathematical analysis) Diffusion wavelets Linear function List of mathematics-based methods Dynamic programming Eigenvalues and eigenvectors Optimal control Orthogonal basis Graph Diagonal matrix Feature (machine learning) Stochastic control Markov decision process Random walk Reinforcement learning Optimal decisions
has abstract	In machine learning, automatic basis function construction (or basis discovery) is the mathematical method of looking for a set of task-independent basis functions that map the state space to a lower-dimensional embedding, while still representing the value function accurately. Automatic basis construction is independent of prior knowledge of the domain, which allows it to perform well where expert-constructed basis functions are difficult or impossible to create. (en)
foaf:isPrimaryTopicOf	http://en.wikipedia.org/wiki/Automatic_basis_function_construction
is Wikipage redirect of	Automatic Basis Function Construction
is Link from a Wikipage to another Wikipage of	Automatic Basis Function Construction List of mathematics-based methods
is foaf:primaryTopic of	http://en.wikipedia.org/wiki/Automatic_basis_function_construction

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