IDEAS home Printed from https://ideas.repec.org/r/plo/pone00/0087357.html

Mutual Information between Discrete and Continuous Data Sets

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Hasan T Abbas & Lejla Alic & Madhav Erraguntla & Jim X Ji & Muhammad Abdul-Ghani & Qammer H Abbasi & Marwa K Qaraqe, 2019. "Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-11, December.
  2. Lunacek, Monte & Williams, Lindy & Severino, Joseph & Ficenec, Karen & Ugirumurera, Juliette & Eash, Matthew & Ge, Yanbo & Phillips, Caleb, 2021. "A data-driven operational model for traffic at the Dallas Fort Worth International Airport," Journal of Air Transport Management, Elsevier, vol. 94(C).
  3. S. Kumar Reddy Mallidi & Rajeswara Rao Ramisetty, 2025. "Embedded-filter ACO using clustering based mutual information for feature selection," Journal of Combinatorial Optimization, Springer, vol. 49(2), pages 1-30, March.
  4. Xin Dang & Dao Nguyen & Yixin Chen & Junying Zhang, 2021. "A new Gini correlation between quantitative and qualitative variables," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(4), pages 1314-1343, December.
  5. Jonathan M. Craig & Andrew H. Laszlo & Henry Brinkerhoff & Christopher A. Thomas & Sinduja K. Marx & Eric F. Lebo & Sarah J. Abell & Michaela C. Franzi & Jesse R. Huang & Hwanhee C. Kim & Jessica D. C, 2026. "An information theory approach to quantifying the sequence-dependent response of nucleic acid motors with applications to nanopore DNA sequencing," Nature Communications, Nature, vol. 17(1), pages 1-12, December.
  6. Banerjee, Ameet Kumar & Dionisio, Andreia & Pradhan, H.K. & Mahapatra, Biplab, 2021. "Hunting the quicksilver: Using textual news and causality analysis to predict market volatility," International Review of Financial Analysis, Elsevier, vol. 77(C).
  7. Philip Cammin & Jingjing Yu & Stefan Voß, 2023. "Tiered prediction models for port vessel emissions inventories," Flexible Services and Manufacturing Journal, Springer, vol. 35(1), pages 142-169, March.
  8. Joo, Semin & Lee, Yeonha & Song, Seok Ho & Song, Kyusang & Seo, Mi Ro & Kim, Sung Joong & Lee, Jeong Ik, 2025. "Leveraging explainable AI for reliable prediction of nuclear power plant severe accident progression," Reliability Engineering and System Safety, Elsevier, vol. 264(PA).
  9. Trizoglou, Pavlos & Liu, Xiaolei & Lin, Zi, 2021. "Fault detection by an ensemble framework of Extreme Gradient Boosting (XGBoost) in the operation of offshore wind turbines," Renewable Energy, Elsevier, vol. 179(C), pages 945-962.
  10. Ao Kong & Robert Azencott & Hongliang Zhu & Xindan Li, 2020. "Pattern recognition in micro-trading behaviors before stock price jumps: A framework based on multivariate time series analysis," Papers 2011.04939, arXiv.org, revised Feb 2021.
  11. repec:iim:iimawp:14638 is not listed on IDEAS
  12. Md Fahim Anjum & Clay Smyth & Rafael Zuzuárregui & Derk Jan Dijk & Philip A. Starr & Timothy Denison & Simon Little, 2024. "Multi-night cortico-basal recordings reveal mechanisms of NREM slow-wave suppression and spontaneous awakenings in Parkinson’s disease," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
  13. María Isabel Arango & Edier Aristizábal & Federico Gómez, 2021. "Morphometrical analysis of torrential flows-prone catchments in tropical and mountainous terrain of the Colombian Andes by machine learning techniques," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(1), pages 983-1012, January.
  14. Marta Niedostatek & Anthony Baptista & Jun Yamamoto & Jürgen Kurths & Ruben Sanchez Garcia & Ben D. MacArthur & Ginestra Bianconi, 2025. "Mining higher-order triadic interactions," Nature Communications, Nature, vol. 16(1), pages 1-11, December.
  15. Zaghloul, Maha & Barakat, Sherif & Rezk, Amira, 2024. "Predicting E-commerce customer satisfaction: Traditional machine learning vs. deep learning approaches," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
  16. Alec S. Dyer & MacKenzie Mark-Moser & Rodrigo Duran & Jennifer R. Bauer, 2024. "Offshore application of landslide susceptibility mapping using gradient-boosted decision trees: a Gulf of Mexico case study," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(7), pages 6223-6244, May.
  17. Wei, Yupeng & Wu, Dazhong, 2023. "Prediction of state of health and remaining useful life of lithium-ion battery using graph convolutional network with dual attention mechanisms," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
  18. Yu-Wen Chen & Yi-Chun Li & Chien-Yu Huang & Chia-Jung Lin & Chia-Jui Tien & Wen-Shiang Chen & Chia-Ling Chen & Keh-Chung Lin, 2023. "Predicting Arm Nonuse in Individuals with Good Arm Motor Function after Stroke Rehabilitation: A Machine Learning Study," IJERPH, MDPI, vol. 20(5), pages 1-12, February.
  19. Tommaso Colombo & Massimiliano Mangone & Andrea Bernetti & Marco Paoloni & Valter Santilli & Laura Palagi, 2019. "Supervised and unsupervised learning to classify scoliosis and healthy subjects based on non-invasive rasterstereography analysis," DIAG Technical Reports 2019-08, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
  20. Wang, Weicheng & Chen, Jinglong & Zhang, Tianci & Liu, Zijun & Wang, Jun & Zhang, Xinwei & He, Shuilong, 2023. "An asymmetrical graph Siamese network for one-classanomaly detection of engine equipment with multi-source fusion," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
  21. José Ferreira & Roya Darabi & Armando Sousa & Frank Brueckner & Luís Paulo Reis & Ana Reis & João Manuel R. S. Tavares & João Sousa, 2026. "Gen-JEMA: enhanced explainability using generative joint embedding multimodal alignment for monitoring directed energy deposition," Journal of Intelligent Manufacturing, Springer, vol. 37(4), pages 1633-1658, April.
  22. Xiaobo Yang & Zhilong Mi & Qingcai He & Binghui Guo & Zhiming Zheng, 2023. "Identification of Vital Genes for NSCLC Integrating Mutual Information and Synergy," Mathematics, MDPI, vol. 11(6), pages 1-15, March.
  23. Ahmadi, Arman & Kazemi, Mohammad Hossein & Daccache, Andre & Snyder, Richard L., 2024. "SolarET: A generalizable machine learning approach to estimate reference evapotranspiration from solar radiation," Agricultural Water Management, Elsevier, vol. 295(C).
  24. Teng, Huei-Wen & Kang, Ming-Hsuan & Lee, I-Han & Bai, Le-Chi, 2024. "Bridging accuracy and interpretability: A rescaled cluster-then-predict approach for enhanced credit scoring," International Review of Financial Analysis, Elsevier, vol. 91(C).
  25. Ao Kong & Robert Azencott & Hongliang Zhu & Xindan Li, 2024. "Pattern Recognition in Microtrading Behaviors Preceding Stock Price Jumps: A Study Based on Mutual Information for Multivariate Time Series," Computational Economics, Springer;Society for Computational Economics, vol. 63(4), pages 1401-1429, April.
  26. Christopher A. Thomas & Henry Brinkerhoff & Jonathan M. Craig & Shuichi Hoshika & Desislava Mihaylova & Akira M. Pfeffer & Michaela C. Franzi & Sarah J. Abell & Jessica D. Carrasco & Jens H. Gundlach , 2025. "Sequencing a DNA analog composed of artificial bases," Nature Communications, Nature, vol. 16(1), pages 1-11, December.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.