References in zbMATH (referenced in 1043 articles )

Showing results 1 to 20 of 1043.
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  1. Boullé, Marc; Charnay, Clément; Lachiche, Nicolas: A scalable robust and automatic propositionalization approach for Bayesian classification of large mixed numerical and categorical data (2019)
  2. Bruni, Renato; Bianchi, Gianpiero; Dolente, Cosimo; Leporelli, Claudio: Logical analysis of data as a tool for the analysis of probabilistic discrete choice behavior (2019)
  3. Karaca, Yeliz; Cattani, Carlo: Computational methods for data analysis (2019)
  4. Ramasubramanian, Karthik; Singh, Abhishek: Machine learning using R. With time series and industry-based use cases in R (2019)
  5. Wang, Lidong; Zhang, Ruijun; Mu, Yashuang: Fu-SulfPred: identification of protein S-sulfenylation sites by fusing forests via Chou’s general PseAAC (2019)
  6. Aggarwal, Charu C.: Machine learning for text (2018)
  7. Alsolami, Fawaz; Amin, Talha; Chikalov, Igor; Moshkov, Mikhail: Bi-criteria optimization problems for decision rules (2018)
  8. Angelino, Elaine; Larus-Stone, Nicholas; Alabi, Daniel; Seltzer, Margo; Rudin, Cynthia: Learning certifiably optimal rule lists for categorical data (2018)
  9. Au, Timothy C.: Random forests, decision trees, and categorical predictors: the “absent levels” problem (2018)
  10. Bakhach, Amer; Chinthalapati, Venkata L. Raju; Tsang, Edward P. K.; El Sayed, Abdul Rahman: Intelligent dynamic backlash agent: a trading strategy based on the directional change framework (2018)
  11. Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail: Bi-criteria optimization of decision trees with applications to data analysis (2018)
  12. Ignatiev, Alexey; Pereira, Filipe; Narodytska, Nina; Marques-Silva, Joao: A SAT-based approach to learn explainable decision sets (2018)
  13. Oztekin, Asil: Creating a marketing strategy in healthcare industry: a holistic data analytic approach (2018)
  14. Pota, Marco; Esposito, Massimo; De Pietro, Giuseppe: Likelihood-fuzzy analysis: from data, through statistics, to interpretable fuzzy classifiers (2018)
  15. Qu, Yanpeng; Shang, Changjing; Parthaláin, Neil Mac; Wu, Wei; Shen, Qiang: Multi-functional nearest-neighbour classification (2018)
  16. Rudin, Cynthia; Ertekin, Şeyda: Learning customized and optimized lists of rules with mathematical programming (2018)
  17. Scott, Ryan; MacPherson, Brian; Gras, Robin: A comparison of stable and fluctuating resources with respect to evolutionary adaptation and life-history traits using individual-based modeling and machine learning (2018)
  18. Vilas Boas, Matheus Guedes; Santos, Haroldo Gambini; de Campos Merschmann, Luiz Henrique: Optimal decision trees for feature based parameter tuning: integer programming model and VNS heuristic (2018)
  19. Villmann, T.; Kaden, M.; Hermann, W.; Biehl, M.: Learning vector quantization classifiers for ROC-optimization (2018)
  20. Wang, Di; Zhang, Zuoquan; Bai, Rongquan; Mao, Yanan: A hybrid system with filter approach and multiple population genetic algorithm for feature selection in credit scoring (2018)

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