Quantum K-Means Clustering

This repository implements the K-means clustering algorithm using quantum state encoding for classical data points and encodes them to Quantum.

⚛️ Functions

1. generate_random_data: Generates a NumPy array of random data with one column .

2. ground_state: Returns a NumPy array representing the ground state (|0> state).

3. initialize_centroids: Randomly initializes k centroids from the data points.

4. encode_data: Encodes classical data points into quantum states using an RXGate.

5. findClosestCentroids: Computes the centroid memberships for every encoded data point.

6. computeCentroids: Returns the new centroids by computing the means of the data points assigned to each centroid.

7. K_means_Quantum_clustering: Performs K-means clustering on classical data points using quantum state encoding.