WEKA: Waikato Environment for Knowledge Analysis. WEKA is a popular machine learning workbench with a development life of nearly two decades. This article provides an overview of the factors that we believe to be important to its success. Rather than focussing on the software’s functionality, we review aspects of project management and historical development decisions that likely had an impact on the uptake of the project.

References in zbMATH (referenced in 307 articles , 1 standard article )

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  1. Gao, Can; Wang, Zhicheng; Zhou, Jie: Three-way approximate reduct based on information-theoretic measure (2022)
  2. Müller, David; Müller, Marcus G.; Kress, Dominik; Pesch, Erwin: An algorithm selection approach for the flexible job shop scheduling problem: choosing constraint programming solvers through machine learning (2022)
  3. Acar, Müge; Kasimbeyli, Refail: A polyhedral conic functions based classification method for noisy data (2021)
  4. Bakirov, Rashid; Fay, Damien; Gabrys, Bogdan: Automated adaptation strategies for stream learning (2021)
  5. Ballı, Serkan; Özdemir, Engin: A novel method for prediction of EuroLeague game results using hybrid feature extraction and machine learning techniques (2021)
  6. Gao, Can; Zhou, Jie; Miao, Duoqian; Wen, Jiajun; Yue, Xiaodong: Three-way decision with co-training for partially labeled data (2021)
  7. Hamed, Ahmed; Sobhy, Ahmed; Nassar, Hamed: Distributed approach for computing rough set approximations of big incomplete information systems (2021)
  8. Ignatiev, Alexey; Marques-Silva, Joao: SAT-based rigorous explanations for decision lists (2021)
  9. Jain, Pankhuri; Tiwari, Anoop Kumar; Som, Tanmoy: Enhanced prediction of anti-tubercular peptides from sequence information using divergence measure-based intuitionistic fuzzy-rough feature selection (2021)
  10. Malan, Katherine M.: Online landscape analysis for guiding constraint handling in particle swarm optimisation (2021)
  11. Maliah, Shlomi; Shani, Guy: Using POMDPs for learning cost sensitive decision trees (2021)
  12. Pang, Guansong; Cao, Longbing; Chen, Ling: Homophily outlier detection in non-IID categorical data (2021)
  13. Pięta, Piotr; Szmuc, Tomasz: Applications of rough sets in big data analysis: an overview (2021)
  14. Rezaei, Mostafa; Cribben, Ivor; Samorani, Michele: A clustering-based feature selection method for automatically generated relational attributes (2021)
  15. Şahin, Durmuş Özkan; Akleylek, Sedat; Kılıç, Erdal: On the effect of (k) values and distance metrics in KNN algorithm for android malware detection (2021)
  16. Tamanna, Tasmi; Rahman, Md Anisur; Sultana, Samia; Haque, Mohammad Hasibul; Parvez, Mohammad Zavid: Predicting seizure onset based on time-frequency analysis of EEG signals (2021)
  17. Aguilera, Ana; Subero, Alberto: Automatic gait classification patterns in spastic hemiplegia (2020)
  18. Anthony D. Blaom, Franz Kiraly, Thibaut Lienart, Yiannis Simillides, Diego Arenas, Sebastian J. Vollmer: MLJ: A Julia package for composable Machine Learning (2020) arXiv
  19. Bain, Travaughn C.; Avila-Herrera, Juan F.; Subasi, Ersoy; Subasi, Munevver Mine: Logical analysis of multiclass data with relaxed patterns (2020)
  20. Boughaci, Dalila; Alkhawaldeh, Abdullah A. K.: Appropriate machine learning techniques for credit scoring and bankruptcy prediction in banking and finance: a comparative study (2020)

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Further publications can be found at: http://www.cs.waikato.ac.nz/ml/publications.html