Dataset and source code for ensemble learning model for imbalanced data based on PQK-Z quantum-inspired feature mapping

This record contains benchmark tabular imbalanced datasets and Python source code to reproduce all experiments in the manuscript "An Ensemble Learning Model for Imbalanced Data Based on PQK-Z Quantum-inspired Feature Mapping". The datasets are public benchmark imbalanced datasets used for model training, validation and testing. The source code implements the PQK-Z quantum-inspired feature mapping, ensemble learning framework, stratified K-fold cross validation, ablation experiments, and statistical significance tests including Wilcoxon and Friedman test. The README file describes the folder structure, Python environment, package versions and step-by-step instructions to reproduce the experimental results, evaluation metrics (Recall, F1, AUC). Dataset is licensed under CC0 1.0 Universal. The source code is released under MIT License.