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qTLCA as a Hybrid Quantum Classical Algorithm for Structural Missing Data in Longitudinal Datasets Using ZZFeatureMap Kernel Design and Uncertainty Flag Encoding with Application to Student Performance Profiling

2026-06-01

Abstract excerpt

<title>Abstract</title> <p>Longitudinal datasets with structural missing data where missingness is caused by the outcome variable being studied rather than random non-response pose a fundamental challenge for classical clustering algorithms. Standard imputation methods introduce distributional bias precisely when it matters most, undermining the reliability of any downstream analysis. This paper introduces qTLCA,...

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Literature Corpus work: adfa29e1-151b-5dd0-a198-32219bf752b5
DOI: 10.21203/rs.3.rs-9588213/v1

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qTLCA as a Hybrid Quantum Classical Algorithm for Structural Missing Data in Longitudinal Datasets Using ZZFeatureMap Kernel Design and Uncertainty Flag Encoding with Application to Student Performance ProfilingDOI 10.21203/rs.3.rs-9588213/v1Read

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