Adaptive k-Nearest Neighbor Classifier Based on Local Curvature Estimation
Computes balanced accuracy.
Computes the curvatures of all samples in the training set.
Computes the F1-score.
Adaptive k-Nearest Neighbor Classifier
Computes the curvature of a single test sample's neighborhood.
Quantizes real values to integer levels.
A helper sigmoid function.
Standard k-NN classifier.
Implements the kK-NN algorithm, an adaptive k-nearest neighbor classifier that adjusts the neighborhood size based on local data curvature. The method estimates local Gaussian curvature by approximating the shape operator of the data manifold. This approach aims to improve classification performance, particularly in datasets with limited samples.