# Dataset attribution This bundle contains unmodified data files from two datasets distributed by the UCI Machine Learning Repository under the [Creative Commons Attribution 4.0 International license](https://creativecommons.org/licenses/by/4.0/) (CC BY 4.0). ## HTRU2 - Dataset: Robert Lyon (2015), *HTRU2*, UCI Machine Learning Repository. - DOI: - UCI record: - Official archive: - Included unmodified files: `data/HTRU_2.csv` and `data/Readme.txt`. - License: CC BY 4.0, as recorded by UCI. - Requested paper citation: R. J. Lyon, B. W. Stappers, S. Cooper, J. M. Brooke, and J. D. Knowles (2016), "Fifty years of pulsar candidate selection: from simple filters to a new principled real-time classification approach," *Monthly Notices of the Royal Astronomical Society*. The original `Readme.txt` is retained because it documents the raw column order, class encoding, study context, and acknowledgements. The feature names used by the analysis follow that file's order. ## Rice (Cammeo and Osmancik) - Dataset: Ilkay Cinar and Murat Koklu (2019), *Rice (Cammeo and Osmancik)*, UCI Machine Learning Repository. - DOI: - UCI record: - Official archive: - Included unmodified files: `data/Rice_Cammeo_Osmancik.arff` and `data/Citation_Request.txt`. - License: CC BY 4.0, as recorded by UCI. - Requested paper citation: I. Cinar and M. Koklu (2019), "Classification of Rice Varieties Using Artificial Intelligence Methods," *International Journal of Intelligent Systems and Applications in Engineering*, 7(3), 188-194. `Cammeo` is encoded as the positive class only to make binary probability and average-precision calculations explicit. That convention does not imply that Cammeo is scientifically preferable to Osmancik. ## Reuse The source datasets may be shared and adapted under CC BY 4.0 with appropriate credit. The generated analysis artifacts in this bundle do not replace the dataset records, original readme files, or cited papers.