Packages

p

soul.algorithm

undersampling

package undersampling

Type Members

  1. class BC extends AnyRef

    Balance Cascade algorithm.

    Balance Cascade algorithm. Original paper: "Exploratory Undersampling for Class-Imbalance Learning" by Xu-Ying Liu, Jianxin Wu and Zhi-Hua Zhou.

  2. class CNN extends AnyRef

    Condensed Nearest Neighbor decision rule.

    Condensed Nearest Neighbor decision rule. Original paper: "The Condensed Nearest Neighbor Rule" by P. Hart.

  3. class CPM extends AnyRef

    Class Purity Maximization.

    Class Purity Maximization. Original paper: "An Unsupervised Learning Approach to Resolving the Data Imbalanced Issue in Supervised Learning Problems in Functional Genomics" by Kihoon Yoon and Stephen Kwek.

  4. class ClusterOSS extends AnyRef

    ClusterOSS.

    ClusterOSS. Original paper: "ClusterOSS: a new undersampling method for imbalanced learning." by Victor H Barella, Eduardo P Costa and André C P L F Carvalho.

  5. class EE extends AnyRef

    Easy Ensemble algorithm.

    Easy Ensemble algorithm. Original paper: "Exploratory Undersampling for Class-Imbalance Learning" by Xu-Ying Liu, Jianxin Wu and Zhi-Hua Zhou.

  6. class ENN extends AnyRef

    Edited Nearest Neighbour rule.

    Edited Nearest Neighbour rule. Original paper: "Asymptotic Properties of Nearest Neighbor Rules Using Edited Data" by Dennis L. Wilson.

  7. class EUS extends AnyRef

    Evolutionary Under Sampling.

    Evolutionary Under Sampling. Original paper: "Evolutionary Under-Sampling for Classification with Imbalanced Data Sets: Proposals and Taxonomy" by Salvador Garcia and Francisco Herrera.

  8. class IHTS extends AnyRef

    Instance Hardness Threshold.

    Instance Hardness Threshold. Original paper: "An Empirical Study of Instance Hardness" by Michael R. Smith, Tony Martinez and Christophe Giraud-Carrier.

  9. class IPADE extends AnyRef

    Iterative Instance Adjustment for Imbalanced Domains.

    Iterative Instance Adjustment for Imbalanced Domains. Original paper: "Addressing imbalanced classification with instance generation techniques: IPADE-ID" by Victoria López, Isaac Triguero, Cristóbal J. Carmona, Salvador García and Francisco Herrera.

  10. class NCL extends AnyRef

    Neighbourhood Cleaning Rule.

    Neighbourhood Cleaning Rule. Original paper: "Improving Identification of Difficult Small Classes by Balancing Class Distribution" by J. Laurikkala.

  11. class NM extends AnyRef

    NearMiss.

    NearMiss. Original paper: "kNN Approach to Unbalanced Data Distribution: A Case Study involving Information Extraction" by Jianping Zhang and Inderjeet Mani.

  12. class OSS extends AnyRef

    One-Side Selection.

    One-Side Selection. Original paper: "Addressing the Curse of Imbalanced Training Sets: One-Side Selection" by Miroslav Kubat and Stan Matwin.

  13. class RU extends AnyRef

    Compute a random algorithm.

    Compute a random algorithm. Original paper: "A study of the behavior of several methods for balancing machine learning training data" by Batista, Gustavo EAPA and Prati, Ronaldo C and Monard, Maria Carolina.

  14. class SBC extends AnyRef

    Undersampling Based on Clustering.

    Undersampling Based on Clustering. Original paper: "Under-Sampling Approaches for Improving Prediction of the Minority Class in an Imbalanced Dataset" by Show-Jane Yen and Yue-Shi Lee.

  15. class TL extends AnyRef

    Tomek Link.

    Tomek Link. Original paper: "Two Modifications of CNN" by Ivan Tomek.

Ungrouped