https://github.com/NestorRV/undersampling

A Scala library for undersampling in imbalanced classification.
https://github.com/NestorRV/undersampling

algorithm classification imbalance-learning nearest-neighbor-rules undersampling

Last synced: 3 months ago
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A Scala library for undersampling in imbalanced classification.

• Host: GitHub
• URL: https://github.com/NestorRV/undersampling
• Owner: NestorRV
• License: gpl-3.0
• Created: 2017-11-19T12:19:42.000Z (almost 7 years ago)
• Default Branch: master
• Last Pushed: 2018-06-25T14:35:44.000Z (over 6 years ago)
• Last Synced: 2024-05-16T20:33:20.648Z (6 months ago)
• Topics: algorithm, classification, imbalance-learning, nearest-neighbor-rules, undersampling
• Language: Scala
• Homepage: https://nestorrv.github.io
• Size: 9.63 MB
• Stars: 16
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-imbalanced-learning - **undersampling** - A Scala library for ***under-sampling and their ensemble variants*** in imbalanced classification. (Uncategorized / Uncategorized)

README

        
# undersampling

### By Néstor Rodríguez Vico

Documentation available in [https://nestorrv.github.io](https://nestorrv.github.io).

Included algorithms:

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

* **Class Purity Maximization algorithm.** 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.

* **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.

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

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

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

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

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

* **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.

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

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

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

* **Random Undersampling.**

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

* **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.