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Logistic Regression

ML Models & Algorithms
An early, simple classification model.

Logistic Regression is a supervised learning algorithm that is classified as a Linear Model. Its core function is to predict probabilities to classify data into two categories (binary classification). The algorithm outputs values between 0 and 1, applying a “logit” function to predict the outcome.
Key benefits include its interpretability and relative ease of explanation. Logistic Regression is commonly used for predicting customer churn, email open rates, or ad engagement. It is also one of the example algorithms suggested for Search Intent Classification.

Related Concepts

Binary Classification Machine Learning (ML) Neural Network Predictive Text Models

Sources & References

Introduction to Machine Learning for SEOs Course
academy.mlforseo.com

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