Difference between revisions of "Inductive bias"

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The inductive bias of a learning algorithm is the set of assumptions that the learner uses to predict outputs given inputs that it has not encountered
 
The inductive bias of a learning algorithm is the set of assumptions that the learner uses to predict outputs given inputs that it has not encountered
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|year = 1980
 
|year = 1980
 
|title = The need for biases in learning generalizations
 
|title = The need for biases in learning generalizations
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|url = http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.120.4179
 
|url = http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.120.4179
 
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In [[Bayesian]] framework, inductive bias is encoded in the [[prior distribution]].
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'''Inductive bias''' refers to your suspicion that if the sun has risen for the last billion days in a row, then it may rise tomorrow as well.  Since it is [[logically possible]] that the laws of physics will arbitrarily cease to work and that the sun will ''not'' rise tomorrow, coming to this conclusion requires an inductively biased [[prior]].
  
==See also==
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This sort of bias is not a bad thing - without "inductive bias" you can't draw any conclusion at all from the data.  It's just a different technical meaning attached to the same word.
*[[Prior distribution]]
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*[[Statistical bias]]
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==Primary post==
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*[http://lesswrong.com/lw/hg/inductive_bias/ "Inductive Bias"]
  
 
==Footnotes==
 
==Footnotes==
 
<references/>
 
<references/>
  
==Blog posts==
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==See also==
*[http://lesswrong.com/lw/hg/inductive_bias/ "Inductive Bias"] by [[Eliezer Yudkowsky]]
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*[[Superexponential conceptspace]]
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*[[Prior distribution]]
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*[[Statistical bias]]
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*[[Cognitive bias]]
  
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[[Category:Machine learning]]

Latest revision as of 05:48, 18 November 2009

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Wikipedia has an article about

The inductive bias of a learning algorithm is the set of assumptions that the learner uses to predict outputs given inputs that it has not encountered

Tom Mitchell[1]

Inductive bias refers to your suspicion that if the sun has risen for the last billion days in a row, then it may rise tomorrow as well. Since it is logically possible that the laws of physics will arbitrarily cease to work and that the sun will not rise tomorrow, coming to this conclusion requires an inductively biased prior.

This sort of bias is not a bad thing - without "inductive bias" you can't draw any conclusion at all from the data. It's just a different technical meaning attached to the same word.

Primary post

Footnotes

See also