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Logistic Regression is a supervised machine learning algorithm used for classification tasks. It predicts the probability that a data instance belongs to a particular class by applying the sigmoid function to a linear combination of input features. Unlike linear regression, which predicts continuous values, logistic regression is designed to classify data into categories such as Yes/No, True/False, or different class labels. It is widely used in applications such as disease prediction, spam email detection, customer churn prediction, and sentiment analysis because of its simplicity, efficiency, and interpretability. For implementing Logistic Regression in Python, the Iris dataset is chosen. The Iris dataset is one of the most popular datasets for classification problems. ______ _____ _______ _______ ________ ______ ___ _______ _______.
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