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 94 articles )

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  1. Alanazi, Fadhah Amer: A mixture of regular vines for multiple dependencies (2021)
  2. Blanco, Victor; Puerto, Justo; Rodriguez-Chia, Antonio M.: On (\ell_p)-support vector machines and multidimensional kernels (2020)
  3. Chaabane, Ikram; Guermazi, Radhouane; Hammami, Mohamed: Enhancing techniques for learning decision trees from imbalanced data (2020)
  4. Chakraborty, Saptarshi; Paul, Debolina; Das, Swagatam: Hierarchical clustering with optimal transport (2020)
  5. Kerr-Wilson, Jeremy; Pedrycz, Witold: Generating a hierarchical fuzzy rule-based model (2020)
  6. Lázaro, Marcelino; Herrera, Francisco; Figueiras-Vidal, Aníbal R.: Ensembles of cost-diverse Bayesian neural learners for imbalanced binary classification (2020)
  7. Manukyan, Artür; Ceyhan, Elvan: Classification using proximity catch digraphs (2020)
  8. 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)
  9. Wu, Chengyuan; Ren, Shiquan; Wu, Jie; Xia, Kelin: Discrete Morse theory for weighted simplicial complexes (2020)
  10. Blachnik, Marcin: Ensembles of instance selection methods: a comparative study (2019)
  11. Dubnov, Yuriĭ A.: Entropy-based estimation in classification problems (2019)
  12. Panagopoulos, Orestis P.; Xanthopoulos, Petros; Razzaghi, Talayeh; Şeref, Onur: Relaxed support vector regression (2019)
  13. Tanveer, M.; Sharma, A.; Suganthan, P. N.: General twin support vector machine with pinball loss function (2019)
  14. Wang, Biao; Mao, Zhizhong; Huang, Keke: Detecting outliers for complex nonlinear systems with dynamic ensemble learning (2019)
  15. Zhang, Xueying; Li, Ruixian; Zhang, Bo; Yang, Yunxiang; Guo, Jing; Ji, Xiang: An instance-based learning recommendation algorithm of imbalance handling methods (2019)
  16. Zhang, Yongshan; Wu, Jia; Cai, Zhihua; Du, Bo; Yu, Philip S.: An unsupervised parameter learning model for RVFL neural network (2019)
  17. Chakraborty, Saptarshi; Das, Swagatam: Simultaneous variable weighting and determining the number of clusters -- a weighted Gaussian means algorithm (2018)
  18. Cózar, Javier; delaOssa, Luis; Gámez, José A.: Learning compact zero-order TSK fuzzy rule-based systems for high-dimensional problems using an apriori (+) local search approach (2018)
  19. dos Santos, Alex Santana; Valle, Marcos Eduardo: Max-plus and min-plus projection autoassociative morphological memories and their compositions for pattern classification (2018)
  20. Eichner, Martin (ed.); Halloran, M. Elizabeth (ed.); O’Neill, Philip D. (ed.): Design and analysis of infectious disease studies. Abstracts from the workshop held February 18--24, 2018 (2018)

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