@@ -150,16 +150,16 @@ minimal (but useless) implementation, see the implementation of `SmallLearner`
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### List of methods
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- - [ ` fit ` ] (@ref fit ): for (i) training or updating learners that generalize to new data; or
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- (ii) wrapping ` learner ` in an object that is possibly mutated by ` predict ` / ` transform ` ,
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- to record byproducts of those operations, in the special case of * non-generalizing *
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- learners (called here [ static algorithms] (@ref static_algorithms))
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+ - [ ` fit ` ] (@ref fit_docs ): for (i) training or updating learners that generalize to new
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+ data; or (ii) wrapping ` learner ` in an object that is possibly mutated by
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+ ` predict ` / ` transform ` , to record byproducts of those operations, in the special case of
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+ * non-generalizing * learners (called here [ static algorithms] (@ref static_algorithms))
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- - [ ` update ` ] (@ref fit ): for updating learning outcomes after hyperparameter changes, such
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- as increasing an iteration parameter.
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+ - [ ` update ` ] (@ref fit_docs ): for updating learning outcomes after hyperparameter changes,
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+ such as increasing an iteration parameter.
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- - [ ` update_observations ` ] (@ref fit ), [ ` update_features ` ] (@ref fit ): update learning
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- outcomes by presenting additional training data.
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+ - [ ` update_observations ` ] (@ref fit_docs ), [ ` update_features ` ] (@ref fit_docs ): update
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+ learning outcomes by presenting additional training data.
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- [ ` predict ` ] (@ref operations): for outputting [ targets] (@ref proxy) or [ target
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proxies] (@ref proxy) (such as probability density functions)
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