The Improvement of Decision Tree Construction Algorithm Based On Quantum Heuristic Algorithms

TL;DR

This paper explores enhancing decision tree construction by integrating quantum heuristic algorithms, specifically QAOA, and compares classical and quantum implementations to evaluate improvements.

Contribution

It introduces a quantum heuristic-based decision tree construction algorithm and demonstrates its implementation and comparison with classical methods.

Findings

Quantum heuristic algorithms can improve decision tree construction.

Quantum and classical implementations show comparable performance.

The study provides a foundation for quantum-enhanced machine learning algorithms.

Abstract

This work is related to the implementation of a decision tree construction algorithm on a quantum simulator. Here we consider an algorithm based on a binary criterion. Also, we study the improvement capability with quantum heuristic QAOA. We implemented the classical and the quantum version of this algorithm to compare built trees.