Quantum-Inspired Applications for Classification Problems

In the context of quantum-inspired machine learning, quantum state discrimination is
a useful tool for classification problems. We implement a local approach combining the k-nearest
neighbors algorithm with some quantum-inspired classifiers. We compare the performance with
respect to well-known classifiers applied to benchmark datasets.