The python sklearn.linear_model.LogisticRegression module is a part of the scikit-learn library, which provides a machine learning implementation of the logistic regression algorithm. Logistic regression is a statistical model used for binary classification problems, where the goal is to predict one of two possible outcomes based on a set of input features. This module allows users to fit a logistic regression model to their data, tune its parameters, and make predictions on new data. It also provides various methods for interpreting the model, such as accessing the coefficients and intercept, calculating probabilities, and evaluating the model's performance. With the logistic regression module in scikit-learn, users can efficiently and effectively build predictive models for binary classification tasks.
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