Detailed results of Multilabel Prototype Generation for Data Reduction in k-Nearest Neighour classification
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资源简介：
Detailed experimental results of both the proposed and existing multilabel Prototype Generation methods for Data Reduction in k-Nearest Neighbour classification:
1. General Multilabel PG comparative
- General comparison of the proposed methods against the existing proposals in the literature.
- Individual results provided for each corpus.
- Corresponds to Section 5.1 in the manuscript.
2. Noise robustness
- Study of the noise robustness capabilities of the proposed strategies as well as the existing methods.
- Individual results provided for each corpus.
- Corresponds to Section 5.2 in the manuscript.
3. Imbalanced data
- Assessment considering imbalanced data metrics.
- Individual results provided for each corpus.
- Corresponds to Section 5.3 in the manuscript.
4. Execution time bechmarking
- Benchmarking comparative, in terms of execution time, of the assessed methods.
- Individual results provided for each iteration considered.
- Corresponds to Section 5.4 in the manuscript.
创建时间：
2025-03-20
