By the same authors

From the same journal

Quantum decision tree classifier

Research output: Contribution to journalArticle

Published copy (DOI)

Author(s)

Department/unit(s)

Publication details

JournalQuantum Information Processing
DatePublished - Mar 2014
Issue number3
Volume13
Number of pages14
Pages (from-to)757-770
Original languageEnglish

Abstract

We study the quantum version of a decision tree classifier to fill the gap between quantum computation and machine learning. The quantum entropy impurity criterion which is used to determine which node should be split is presented in the paper. By using the quantum fidelity measure between two quantum states, we cluster the training data into subclasses so that the quantum decision tree can manipulate quantum states. We also propose algorithms constructing the quantum decision tree and searching for a target class over the tree for a new quantum object.

Discover related content

Find related publications, people, projects, datasets and more using interactive charts.

View graph of relations