Inductive bias
From Lesswrongwiki
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.
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Footnotes
- ↑ Tom M. Mitchell (1980) (PDF). The need for biases in learning generalizations. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.120.4179.