Data for: Tree-Based Space Partition and Merging Ensemble Learning Framework for Imbalanced Problems

Published: 1 Jul 2019 | Version 1 | DOI: 10.17632/dfndb33597.1
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Description of this data

In the experiment of imbalanced problems, 50 imbalanced data sets from the Knowledge Extraction based on Evolutionary Learning (KEEL: http://www.keel.es/) are used in this paper. Every data set is a 5x3 cell with 5 rows and 3 columns. Every row corresponds to the data in one fold of the 5-folds cross-validation. The first column is the training data of minority class. The second column is the training data of majority class. The last column is the testing data. For all detailed sample in corresponding element, the last column is the label.

Experiment data files

This data is associated with the following publication:

Tree-based space partition and merging ensemble learning framework for imbalanced problems

Published in: Information Sciences

Latest version

  • Version 1

    2019-07-01

    Published: 2019-07-01

    DOI: 10.17632/dfndb33597.1

    Cite this dataset

    Wang, Zhe (2019), “Data for: Tree-Based Space Partition and Merging Ensemble Learning Framework for Imbalanced Problems”, Mendeley Data, v1 http://dx.doi.org/10.17632/dfndb33597.1

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The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.

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This dataset is licensed under a Creative Commons Attribution 4.0 International licence. What does this mean? You can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.

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