Systems and methods for decision tree construction and update using quantum algorithms

A system, comprising:

• a classical computer executing a classical computer program;
• and
• a quantum computer in communication with the classical computer program;
• wherein:
• the classical computer program is configured to receive a dataset comprising a plurality of training examples, each of the plurality of training examples having a plurality of features;
• the classical computer program is configured to load the dataset into a quantum accessible data structure;
• the classical computer program is configured to provide the quantum accessible data structure to the quantum computer;
• the quantum computer is configured to perform quantum estimation of a Pearson correlation coefficient on the dataset in the quantum accessible data structure to create a weighted dataset;
• the quantum computer program is configured to perform supervised quantum clustering of each of the plurality of training examples in the weighted dataset into one of a plurality of clusters;
• and
• the classical computer program is configured to select a label for each of the plurality of clusters.