The design and implementation of an automated botanical classification system using the Iris dataset. By employing Logistic Regression enhanced with the "Perceptron Trick" (polynomial feature expansion) and Sigmoid activation functions, three species: Setosa, Versicolor, and Virginica. The implementation bridges the gap between basic linear classifiers and sophisticated probabilistic models, focusing on feature scaling, non linear decision boundaries, and statistical validation.

2026