Logistic regression predicts the probability that an example belongs to a class — the foundational classification algorithm.

How It Works

Despite the name, it's a classification algorithm. It applies a sigmoid function to a linear equation to output a probability between 0 and 1.

When to Use It

• Spam detection (spam or not spam)
• Disease diagnosis (positive or negative)
• Click prediction (click or not click)

Decision Boundary

Typically set at 0.5 — outputs above 0.5 classified as positive. Adjusting this threshold trades off precision vs recall.

Evaluation

Accuracy, precision, recall, F1 score, AUC-ROC.

Reference:

Logistic regression tutorial

https://developers.google.com/machine-learning/crash-course/logistic-regression