Polyadic Quantum Classifier

Understand

We introduce here a supervised quantum machine learning algorithm for multi-class classification on NISQ architectures.

• A parametric quantum circuit is trained to output a specific bit string corresponding to the class of the input datapoint.
• We train and test it on an IBMq 5-qubit quantum computer and the algorithm shows good accuracy --compared to a classical machine learning model-- for ternary classification of the Iris dataset and an extension of the XOR problem.
• Furthermore, we evaluate with simulations how the algorithm fares for a binary and a quaternary classification on resp.