@@ -141,8 +141,8 @@ model = fit(learner, data)
141141model = update_observations(model, new_data, epochs => 12, learning_rate => 0.1)
142142```
143143
144- When following the call `fit(learner, data)`, the `update` call is semantically
145- equivalent to retraining ab initio using a concatenation of `data` and `new_data`,
144+ When following the call `fit(learner, data)`, the `update` call is semantically equivalent
145+ to retraining ab initio using an observation-wise concatenation of `data` and `new_data`,
146146*provided there are no hyperparameter replacements* (which rules out the example
147147above). Behaviour is otherwise learner-specific.
148148
@@ -178,9 +178,9 @@ Return an updated version of the `model` object returned by a previous [`fit`](@
178178`update` call given the new features encapsulated in `new_data`. One may additionally
179179specify hyperparameter replacements in the form `:p1 => value1, :p2 => value2, ...`.
180180
181- When following the call `fit(learner, data)`, the `update ` call is semantically
182- equivalent to retraining ab initio using a concatenation of `data` and `new_data`,
183- *provided there are no hyperparameter replacements.* Behaviour is otherwise
181+ When following the call `fit(learner, data)`, the `update_features ` call is semantically
182+ equivalent to retraining ab initio using a feature-wise concatenation of `data` and
183+ `new_data`, *provided there are no hyperparameter replacements.* Behaviour is otherwise
184184learner-specific.
185185
186186See also [`fit`](@ref), [`update`](@ref), [`update_features`](@ref).
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