WEKA

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 304 articles , 1 standard article )

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  1. Cadenas, Jose M.; Garrido, M. Carmen; Martínez, Raquel; Bonissone, Piero P.: OFP_CLASS: a hybrid method to generate optimized fuzzy partitions for classification (2012) ioport
  2. Catania, Barbara; Maddalena, Anna: A unified framework for heterogeneous patterns (2012) ioport
  3. Choi, Sungbin; Ryu, Borim; Yoo, Sooyoung; Choi, Jinwook: Combining relevancy and methodological quality into a single ranking for evidence-based medicine (2012) ioport
  4. Díez-Pastor, José-Francisco; Bustillo, Andres; Quintana, Guillem; García-Osorio, César: Boosting projections to improve surface roughness prediction in high-torque milling operations (2012) ioport
  5. Dor, Ofer; Reich, Yoram: Strengthening learning algorithms by feature discovery (2012) ioport
  6. Fürnkranz, Johannes; Hüllermeier, Eyke; Cheng, Weiwei; Park, Sang-Hyeun: Preference-based reinforcement learning: a formal framework and a policy iteration algorithm (2012)
  7. Ivanescu, Anca Maria; Wichterich, Marc; Beecks, Christian: The ClasSi coefficient for the evaluation of ranking quality in the presence of class similarities (2012)
  8. Khosravi, Hassan; Schulte, Oliver; Hu, Jianfeng; Gao, Tianxiang: Learning compact Markov logic networks with decision trees (2012) ioport
  9. Kotinis, Miltiadis; Kulkarni, Amit: Multi-objective shape optimization of transonic airfoil sections using swarm intelligence and surrogate models (2012) ioport
  10. Lara, Óscar D.; Pérez, Alfredo J.; Labrador, Miguel A.; Posada, José D.: Centinela: a human activity recognition system based on acceleration \textitandvital sign data (2012) ioport
  11. Lee, Joonseok; Sun, Mingxuan; Lebanon, Guy: PREA: personalized recommendation algorithms toolkit (2012) ioport
  12. Madjarov, Gjorgji; Gjorgjevikj, Dejan; Džeroski, Sašo: Two stage architecture for multi-label learning (2012) ioport
  13. Madjarov, Gjorgji; Kocev, Dragi; Gjorgjevikj, Dejan; Džeroski, Sašo: An extensive experimental comparison of methods for multi-label learning (2012) ioport
  14. Maggini, Marco; Melacci, Stefano; Sarti, Lorenzo: Learning from pairwise constraints by similarity neural networks (2012) ioport
  15. Marques, Ion; Graña, Manuel: Face recognition with lattice independent component analysis and extreme learning machines (2012) ioport
  16. Mitra, Sushmita; Kundu, Partha Pratim; Pedrycz, Witold: Feature selection using structural similarity (2012) ioport
  17. Nagy, István: Person attribute extraction from the textual parts of web pages (2012)
  18. Namboodiri, Saritha; Giuliani, Alessandro; Nair, Achuthsankar S.; Dhar, Pawan K.: Looking for a sequence based allostery definition: a statistical journey at different resolution scales (2012)
  19. Ni, Chong-Jia; Zhang, Ai-Ying; Liu, Wen-Ju; Xu, Bo: Automatic prosodic break detection and feature analysis (2012) ioport
  20. Noto, Keith; Brodley, Carla; Slonim, Donna: FRaC: a feature-modeling approach for semi-supervised and unsupervised anomaly detection (2012) ioport

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