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Editing: online.md
# Online Learners that implement the Online interface can be trained in batches. Learners of this type are great for when you either have a continuous stream of data or a dataset that is too large to fit into memory. In addition, partial training allows the model to evolve over time. ## Partially Train To partially train an Online learner pass it a training set to its `partial()` method: ```php public partial(Dataset $dataset) : void ``` ```php $folds = $dataset->fold(3); $estimator->train($folds[0]); $estimator->partial($folds[1]); $estimator->partial($folds[2]); ``` !!! note Learner will continue to train as long as you are using the `partial()` method, however, calling `train()` on a trained or partially trained learner will reset it back to baseline first.
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