What is Logistic Regression? What is Recall

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Logistic Regression is a statistical method used to model the probability of a certain event occurring based on one or more predictor variables. Recall is a metric used to evaluate the performance of a classification model.

Logistic Regression is used for binary classification tasks, where the outcome variable is categorical and has two classes.
It estimates the probability that a given input belongs to a certain category.
Recall, also known as sensitivity, is the ratio of true positive predictions to the total number of actual positive instances in a dataset.
It is calculated as Recall = TP / (TP + FN), where TP is true positives and FN is false negatives.
A high recall value indicates that the model is good at identifying positive instances.

What is Logistic Regression? What is Recall

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