Create a Classical-Quantum KNN Classifier Using Qiskit

The $k$ nearest neighbor (KNN) classification is a supervised machine learning algorithm used to classify a sample based on the sample(s) nearest to it.

Qiskit is an open-source quantum computing software development kit (SDK) by IBM Quantum. One of the most popular quantum-computing SDKs, Qiskit allows gate-based implementation of quantum circuits. Moreover, Qiskit has dedicated frameworks for specific applications like finance and simulations.

In this project, we’ll implement a quantum algorithm to perform KNN classification. To achieve this objective, we’ll first create a quantum circuit on which the quantum KNN algorithm will be executed. After that, we’ll encode the dataset to the quantum circuit. Then, we’ll simulate the quantum circuit on a simulator and extract the $k$ nearest neighbor from the simulation results.