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Logistic Regression Classifier

The logistic regression classifier is a linear model for classification, implemented in the scikit-learn library. It estimates the probability of an instance belonging to a specific class by fitting a logistic function to the input data. The model supports various regularization techniques, solvers, and multi-class strategies.

Advantages:​

  • Ease of implementation and effectiveness
  • Computational efficiency
  • Low likelihood of overfitting

Disadvantages:​

  • Struggles with non-linear data
  • Impaired performance due to irrelevant or highly correlated features