Reproduce “Comparative Study of Quantum and Classical Machine Learning Models in Binary Classification” on OpenResearch
Turn your favorite coding agents into research agents that review literature, develop hypotheses, and run experiments.
Universal app for Apple silicon and Intel. Requires macOS 11 or later.
About this paper
Anand Kumar Mishra, Ramanuj Awasthi
The authors compare two quantum classifiers with three classical models on a small breast-cancer classification task. They reduce 30 features to four principal components and evaluate a stratified 150-record sample using a 70/30 split and classical simulation. Logistic Regression reaches 97.8% accuracy; the VQC reaches 88.9% and misses five of 17 malignant cases, limiting findings to this test.
Summary by alphaXiv.
Tip: change arxiv.org to autoarxiv.org in any arXiv abstract link to open the paper here.