The sklearn.preprocessing.MinMaxScaler.fit function in Python is used to compute the minimum and maximum values of a given dataset. It learns the range of the features in the dataset and saves them as internal parameters. This information is then used to scale the features of the dataset into a specified range, usually between 0 and 1. This function is typically used in pre-processing stages of machine learning pipelines to normalize the dataset and make it suitable for training machine learning models.
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