KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework
By Jesús Alcalá-Fdez, Alberto Fernández, Julián Luengo, Joaquín Derrac, Salvador Garcia. 2011
2,449 citations recorded by the source corpus.
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Alberto Fernández
- Francisco Herrera
- Salvador Garcia
- Mikel Galar
- Isaac Triguero
- Victoria López
- Jesús Alcalá-Fdez
- Julián Luengo
Citations in the corpus
- Machine Learning and Deep Learning frameworks and libraries for large-scale data mining: a survey (2019, background): “, evolutionary algorithms (Triguero et al. 2017; Alcala-Fdez et al. 2011) and genetic programming (Cano et al.”
- A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches (2012, methodology): “KEEL-dataset repository [57] so that any interested researcher can reproduce the experimental study.”
- The choice of scaling technique matters for classification performance (2022, methodology): “In order to answer these questions and perform further analysis, we modeled an experiment using 82 datasets from the KEEL repository after preprocessing them with five different scaling techniques.”
- A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms (2011, background): “Tool [52,53], researchers can find a module for nonparametric sta-”
- A Fuzzy Association Rule-Based Classification Model for High-Dimensional Problems With Genetic Rule Selection and Lateral Tuning (2011, background): “1The corresponding data partitions (tenfold) for these datasets are available at the KEEL-dataset repository [60]: http://sci2s.”
- A comprehensive data level analysis for cancer diagnosis on imbalanced data (2019, methodology): “All experiments have been developed using the KEEL software [64,65].”
- Analysing the classification of imbalanced data-sets with multiple classes: Binarization techniques and ad-hoc approaches (2013, methodology): “We must point out that the data-set partitions employed in this paper are available for download at the KEEL data-set repository [1] so that any interested researcher can use the same data for comparison.”
- OpenML Benchmarking Suites and the OpenML100 (2017, unknown): “KEEL (Alcala et al., 2010) offers some benchmark data suites, including one for imbalanced classification and one with data sets with missing values.”