The sigmoid function is a mathematical function that produces an S-shaped curve, commonly used to map predicted values between 0 and 1. This characteristic makes it particularly useful in logistic regression for modeling binary outcomes, as it helps transform linear combinations of input variables into probabilities. In the context of logistic regression, the sigmoid function ensures that predictions can be interpreted as probabilities of belonging to a particular class, facilitating decision-making based on these probabilities.
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