Multi-Label Datasets with Missing Values
收藏Zenodo2026-04-17 更新2026-05-26 收录
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https://zenodo.org/doi/10.5281/zenodo.7748932
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资源简介：
Consisting of six multi-label datasets from the UCI Machine Learning repository.
Each dataset contains missing values which have been artificially added at the following rates: 5, 10, 15, 20, 25, and30%. The “amputation” was performed using the “Missing Completely at Random” mechanism.
File names are represented as follows:
amp_DB_MR.arff
where:
DB = original dataset;
MR = missing rate.
If you use any of the resources available here or for more information:
Jacob Junior, A. F. L., do Carmo, F. A., de Santana, A. L., Santana, E. E. C., & Lobato, F. M. F. (2024). EvoImp: Multiple Imputation of Multi-label Classification data with a genetic algorithm. Plos one, 19(1), e0297147. https://doi.org/10.1371/journal.pone.0297147
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Zenodo创建时间：
2023-03-18
