JStatCom

JStatCom is a software framework that makes it easy to integrate numerical procedures written in specialized programming languages, like Matlab, Gauss or Ox, with the Java world. Furthermore, it helps building Graphical User Interfaces (GUI) for mathematical procedures by providing sophisticated data management features that seamlessy interact with Java Swing components.


References in zbMATH (referenced in 98 articles )

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  1. Alanazi, Fadhah Amer: Sequential truncation of (R)-vine copula mixture model for high-dimensional datasets (2021)
  2. Alanazi, Fadhah Amer: A mixture of regular vines for multiple dependencies (2021)
  3. Bagherinia, Ali; Minaei-Bidgoli, Behrooz; Hosseinzadeh, Mehdi; Parvin, Hamid: Reliability-based fuzzy clustering ensemble (2021)
  4. Shahee, Shaukat Ali; Ananthakumar, Usha: An overlap sensitive neural network for class imbalanced data (2021)
  5. Wu, Shuhui; Yu, Mengqing; Ahmed, Moushira Abdallah Mohamed; Qian, Yaguan; Tao, Yuanhong: FL-MAC-RDP: federated learning over multiple access channels with Rényi differential privacy (2021)
  6. Blanco, Victor; Puerto, Justo; Rodriguez-Chia, Antonio M.: On (\ell_p)-support vector machines and multidimensional kernels (2020)
  7. Chaabane, Ikram; Guermazi, Radhouane; Hammami, Mohamed: Enhancing techniques for learning decision trees from imbalanced data (2020)
  8. Chakraborty, Saptarshi; Paul, Debolina; Das, Swagatam: Hierarchical clustering with optimal transport (2020)
  9. Kerr-Wilson, Jeremy; Pedrycz, Witold: Generating a hierarchical fuzzy rule-based model (2020)
  10. Lázaro, Marcelino; Herrera, Francisco; Figueiras-Vidal, Aníbal R.: Ensembles of cost-diverse Bayesian neural learners for imbalanced binary classification (2020)
  11. Manukyan, Artür; Ceyhan, Elvan: Classification using proximity catch digraphs (2020)
  12. Velázquez-Rodríguez, José Luis; Villuendas-Rey, Yenny; Yáñez-Márquez, Cornelio; López-Yáñez, Itzamá; Camacho-Nieto, Oscar: Granulation in rough set theory: a novel perspective (2020)
  13. Wu, Chengyuan; Ren, Shiquan; Wu, Jie; Xia, Kelin: Discrete Morse theory for weighted simplicial complexes (2020)
  14. Blachnik, Marcin: Ensembles of instance selection methods: a comparative study (2019)
  15. Dubnov, Yuriĭ A.: Entropy-based estimation in classification problems (2019)
  16. Panagopoulos, Orestis P.; Xanthopoulos, Petros; Razzaghi, Talayeh; Şeref, Onur: Relaxed support vector regression (2019)
  17. Tanveer, M.; Sharma, A.; Suganthan, P. N.: General twin support vector machine with pinball loss function (2019)
  18. Wang, Biao; Mao, Zhizhong; Huang, Keke: Detecting outliers for complex nonlinear systems with dynamic ensemble learning (2019)
  19. Zhang, Xueying; Li, Ruixian; Zhang, Bo; Yang, Yunxiang; Guo, Jing; Ji, Xiang: An instance-based learning recommendation algorithm of imbalance handling methods (2019)
  20. Zhang, Yongshan; Wu, Jia; Cai, Zhihua; Du, Bo; Yu, Philip S.: An unsupervised parameter learning model for RVFL neural network (2019)

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