Quantum Cognition in Machine Learning

This chapter explores the advantages of quantum cognition machine learning (QCML) over classical techniques, particularly in managing noisy data and sparse datasets. It discusses practical applications of QCML in fields such as cancer research and financial modeling, revealing its effectiveness in making accurate predictions despite incomplete information. By examining the differences in data representation and similarity measures, the chapter highlights how quantum methods outperform traditional approaches in various real-world scenarios.