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Can anyone explain logistic regression in Machine learning?

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Logistic regression in Machine Learning is a supervised algorithm and the most used classification algorithm. Logistic regression predicts the probability of occurrence of the event using a log of odds as the dependent variable. Logistic regression uses a link function called sigmoid function to bring the target variable to 0 to 1 to get the probability of occurrence of an event. In the case of binary classification, if the probability is more than the threshold, we categorize one class otherwise another class.

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