Logistic Regression Skill


Logistic Regression is a widely-used statistical and machine learning method for binary classification tasks, where the outcome variable is categorical and has two classes. Despite its name, logistic regression is used for classification rather than regression.
In logistic regression, the logistic function, also known as the sigmoid function, is applied to a linear combination of input features. The logistic function transforms the linear output into a probability score between 0 and 1, representing the likelihood of belonging to a particular class. The logistic regression model predicts the class with a threshold (commonly 0.5) applied to this probability.Logistic regression is favored for its simplicity, interpretability, and efficiency, making it suitable for applications such as credit scoring, medical diagnosis, and spam filtering. It is a valuable tool in the realm of classification tasks, providing a probabilistic framework for decision-making in various domains.

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