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 107 articles )

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  1. Grbić, Jelena; Wu, Jie; Xia, Kelin; Wei, Guo-Wei: Aspects of topological approaches for data science (2022)
  2. Alanazi, Fadhah Amer: Sequential truncation of (R)-vine copula mixture model for high-dimensional datasets (2021)
  3. Alanazi, Fadhah Amer: A mixture of regular vines for multiple dependencies (2021)
  4. Aminian, Ehsan; Ribeiro, Rita P.; Gama, João: Chebyshev approaches for imbalanced data streams regression models (2021)
  5. Bagherinia, Ali; Minaei-Bidgoli, Behrooz; Hosseinzadeh, Mehdi; Parvin, Hamid: Reliability-based fuzzy clustering ensemble (2021)
  6. Chen, Zhi; Duan, Jiang; Kang, Li; Qiu, Guoping: A hybrid data-level ensemble to enable learning from highly imbalanced dataset (2021)
  7. Geng, Xiaojiao; Liang, Yan; Jiao, Lianmeng: EARC: evidential association rule-based classification (2021)
  8. Grina, Fares; Elouedi, Zied; Lefèvre, Eric: Uncertainty-aware resampling method for imbalanced classification using evidence theory (2021)
  9. Koziarski, Michał; Bellinger, Colin; Woźniak, Michał: RB-CCR: radial-based combined cleaning and resampling algorithm for imbalanced data classification (2021)
  10. Nápoles, Gonzalo; Jastrzȩbska, Agnieszka; Salgueiro, Yamisleydi: Pattern classification with evolving long-term cognitive networks (2021)
  11. Shahee, Shaukat Ali; Ananthakumar, Usha: An overlap sensitive neural network for class imbalanced data (2021)
  12. Soltanzadeh, Paria; Hashemzadeh, Mahdi: RCSMOTE: range-controlled synthetic minority over-sampling technique for handling the class imbalance problem (2021)
  13. 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)
  14. Blanco, Victor; Puerto, Justo; Rodriguez-Chia, Antonio M.: On (\ell_p)-support vector machines and multidimensional kernels (2020)
  15. Chaabane, Ikram; Guermazi, Radhouane; Hammami, Mohamed: Enhancing techniques for learning decision trees from imbalanced data (2020)
  16. Chakraborty, Saptarshi; Paul, Debolina; Das, Swagatam: Hierarchical clustering with optimal transport (2020)
  17. Kadam, Vinod Jagannath; Jadhav, Shivajirao Manikrao: Performance analysis of hyperparameter optimization methods for ensemble learning with small and medium sized medical datasets (2020)
  18. Kerr-Wilson, Jeremy; Pedrycz, Witold: Generating a hierarchical fuzzy rule-based model (2020)
  19. Lázaro, Marcelino; Herrera, Francisco; Figueiras-Vidal, Aníbal R.: Ensembles of cost-diverse Bayesian neural learners for imbalanced binary classification (2020)
  20. Manukyan, Artür; Ceyhan, Elvan: Classification using proximity catch digraphs (2020)

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