The `partial_fit` method in the `sklearn.linear_model.SGDClassifier` is used for incremental training of the classifier on large datasets. It allows the classifier to learn from new batches of data without having to retrain the model from scratch. This method adapts the model's parameters using a stochastic gradient descent algorithm, which makes it efficient for handling large datasets with high dimensions. It updates the model iteratively by processing one batch of data at a time, making it suitable for online learning applications. The `partial_fit` function is commonly used when the entire dataset cannot fit into memory at once or when the dataset is continuously updated.
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