Model: The K-Nearest Neighbors (KNN) model classifies a data point by calculating the Euclidean distance between the input and each instance in the dataset. It then predicts the output based on the majority vote among the \(k\) closest neighbors.
$$ d(\mathbf{x}, \mathbf{x}_i) = \sqrt{\sum_{j=1}^{n} (x_j - x_{ij})^2} $$