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Logistic Regression

Logistic Regression

Logistic Regression is one of the most widely used machine learning algorithms for binary classification problems.

Unlike linear regression, which predicts continuous values, Logistic Regression estimates the probability that a transaction belongs to a particular class.

For example:

  • Probability close to 0 → Genuine transaction
  • Probability close to 1 → Fraudulent transaction

The model uses the relationship between multiple input features and the target variable to determine the likelihood of fraud.

Why Logistic Regression?

  • Simple to understand
  • Fast to train
  • Works well for binary classification
  • Produces probability-based predictions
  • Easy to interpret

Because of these advantages, Logistic Regression is often used as a baseline model for fraud detection systems.