Literatura académica sobre el tema "Evaluation of extreme classifiers"
Crea una cita precisa en los estilos APA, MLA, Chicago, Harvard y otros
Consulte las listas temáticas de artículos, libros, tesis, actas de conferencias y otras fuentes académicas sobre el tema "Evaluation of extreme classifiers".
Junto a cada fuente en la lista de referencias hay un botón "Agregar a la bibliografía". Pulsa este botón, y generaremos automáticamente la referencia bibliográfica para la obra elegida en el estilo de cita que necesites: APA, MLA, Harvard, Vancouver, Chicago, etc.
También puede descargar el texto completo de la publicación académica en formato pdf y leer en línea su resumen siempre que esté disponible en los metadatos.
Artículos de revistas sobre el tema "Evaluation of extreme classifiers"
Balasubramanian, Kishore, and N. P. Ananthamoorthy. "Analysis of hybrid statistical textural and intensity features to discriminate retinal abnormalities through classifiers." Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine 233, no. 5 (2019): 506–14. http://dx.doi.org/10.1177/0954411919835856.
Texto completoMichau, Gabriel, Yang Hu, Thomas Palmé, and Olga Fink. "Feature learning for fault detection in high-dimensional condition monitoring signals." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 234, no. 1 (2019): 104–15. http://dx.doi.org/10.1177/1748006x19868335.
Texto completoAfolabi, Hassan A., and Abdurazzag A. Aburas. "Statistical performance assessment of supervised machine learning algorithms for intrusion detection system." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 1 (2024): 266–77. https://doi.org/10.11591/ijai.v13.i1.pp266-277.
Texto completoAfolabi, Hassan A., and Aburas A. Abdurazzag. "Statistical performance assessment of supervised machine learning algorithms for intrusion detection system." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 1 (2024): 266. http://dx.doi.org/10.11591/ijai.v13.i1.pp266-277.
Texto completoRaza, Ali, Furqan Rustam, Hafeez Ur Rehman Siddiqui, et al. "Predicting Genetic Disorder and Types of Disorder Using Chain Classifier Approach." Genes 14, no. 1 (2022): 71. http://dx.doi.org/10.3390/genes14010071.
Texto completoThiamchoo, Nantarika, and Pornchai Phukpattaranont. "Evaluation of feature projection techniques in object grasp classification using electromyogram signals from different limb positions." PeerJ Computer Science 8 (May 6, 2022): e949. http://dx.doi.org/10.7717/peerj-cs.949.
Texto completoNateghi, Masoud, Mahdi Rahbar Alam, Hossein Amiri, Samaneh Nasiri, and Reza Sameni. "Model-Based Electroencephalogram Instantaneous Frequency Tracking: Application in Automated Sleep–Wake Stage Classification." Sensors 24, no. 24 (2024): 7881. https://doi.org/10.3390/s24247881.
Texto completoTian, Zhang, Chen, Geng, and Wang. "Selective Ensemble Based on Extreme Learning Machine for Sensor-Based Human Activity Recognition." Sensors 19, no. 16 (2019): 3468. http://dx.doi.org/10.3390/s19163468.
Texto completoPeng, Sizhong, Congjun Feng, Zhen Qiu, et al. "Prediction of Lithofacies in Heterogeneous Shale Reservoirs Based on a Robust Stacking Machine Learning Model." Minerals 15, no. 3 (2025): 240. https://doi.org/10.3390/min15030240.
Texto completoTariq, Muhammad Arham, Allah Bux Sargano, Muhammad Aksam Iftikhar, and Zulfiqar Habib. "Comparing Different Oversampling Methods in Predicting Multi-Class Educational Datasets Using Machine Learning Techniques." Cybernetics and Information Technologies 23, no. 4 (2023): 199–212. http://dx.doi.org/10.2478/cait-2023-0044.
Texto completoTesis sobre el tema "Evaluation of extreme classifiers"
Legrand, Juliette. "Simulation and assessment of multivariate extreme models for environmental data." Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPASJ015.
Texto completoLavesson, Niklas. "Evaluation and Analysis of Supervised Learning Algorithms and Classifiers." Licentiate thesis, Karlskrona : Blekinge Institute of Technology, 2006. http://www.bth.se/fou/Forskinfo.nsf/allfirst2/c655a0b1f9f88d16c125714c00355e5d?OpenDocument.
Texto completoNygren, Rasmus. "Evaluation of hyperparameter optimization methods for Random Forest classifiers." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301739.
Texto completoDang, Robin, and Anders Nilsson. "Evaluation of Machine Learning classifiers for Breast Cancer Classification." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-280349.
Texto completoFischer, Manfred M., Sucharita Gopal, Petra Staufer-Steinnocher, and Klaus Steinocher. "Evaluation of Neural Pattern Classifiers for a Remote Sensing Application." WU Vienna University of Economics and Business, 1995. http://epub.wu.ac.at/4184/1/WSG_DP_4695.pdf.
Texto completoAlorf, Abdulaziz Abdullah. "Primary/Soft Biometrics: Performance Evaluation and Novel Real-Time Classifiers." Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/96942.
Texto completoAyhan, Tezer Bahar. "Damage evaluation of civil engineering structures under extreme loadings." Phd thesis, École normale supérieure de Cachan - ENS Cachan, 2013. http://tel.archives-ouvertes.fr/tel-00975488.
Texto completoZuzáková, Barbora. "Exchange market pressure: an evaluation using extreme value theory." Master's thesis, Vysoká škola ekonomická v Praze, 2013. http://www.nusl.cz/ntk/nusl-199589.
Texto completoBuolamwini, Joy Adowaa. "Gender shades : intersectional phenotypic and demographic evaluation of face datasets and gender classifiers." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/114068.
Texto completoPydipati, Rajesh. "Evaluation of classifiers for automatic disease detection in citrus leaves using machine vision." [Gainesville, Fla.] : University of Florida, 2004. http://purl.fcla.edu/fcla/etd/UFE0006991.
Texto completoLibros sobre el tema "Evaluation of extreme classifiers"
Margineantu, Dragos D. Bootstrap methods for the cost-sensitive evaluation of classifiers. Oregon State University, Dept. of Computer Science, 2000.
Buscar texto completoResearch, United States Office of Federal Coordinator for Meteorological Services and Supporting. Report on wind chill temperature and extreme heat indices: Evaluation and improvement projects. U.S. Department of Commerce, National Oceanic and Atmospheric Administration, Office of the Federal Coordinator for Meteorological Services and Supporting Research, 2003.
Buscar texto completoMatin, M. A. Risk assessment and evaluation of probability of extreme hydrological events: Case study from Noakhali Sadar and Subarnachar Upazilas. IUCN Bangladesh Country Office, 2008.
Buscar texto completoMatin, M. A. Risk assessment and evaluation of probability of extreme hydrological events: Case study from Noakhali Sadar and Subarnachar Upazilas. IUCN Bangladesh Country Office, 2008.
Buscar texto completoExtreme Government Makeover: Increasing Our Capacity to Do More Good. Governing Books, 2011.
Buscar texto completoMeacham, Brian J. Extreme Event Mitigation in Buildings; Analysis and Design. National Fire Protection Association, 2006.
Buscar texto completoBush, Kenneth, and Colleen Duggan. Evaluation in the Extreme: Research, Impact and Politics in Violently Divided Societies. SAGE Publications India Pvt, Ltd., 2015.
Buscar texto completoBush, Kenneth, and Colleen Duggan. Evaluation in the Extreme: Research, Impact and Politics in Violently Divided Societies. SAGE Publications India Pvt, Ltd., 2021.
Buscar texto completoEvaluation in the Extreme: Research, Impact and Politics in Violently Divided Societies. SAGE Publications India Pvt, Ltd., 2015.
Buscar texto completoCapítulos de libros sobre el tema "Evaluation of extreme classifiers"
Seewald, Alexander K., and Johannes Fürnkranz. "An Evaluation of Grading Classifiers." In Advances in Intelligent Data Analysis. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44816-0_12.
Texto completoAlonzo, Todd A., and Margaret Sullivan Pepe. "Development and Evaluation of Classifiers." In Topics in Biostatistics. Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-530-5_6.
Texto completoLóczy, Dénes. "Evaluation of Geomorphological Impact." In Geomorphological impacts of extreme weather. Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-6301-2_23.
Texto completoAshok, Pranav, Tomáš Brázdil, Krishnendu Chatterjee, Jan Křetínský, Christoph H. Lampert, and Viktor Toman. "Strategy Representation by Decision Trees with Linear Classifiers." In Quantitative Evaluation of Systems. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30281-8_7.
Texto completoTorzilli, Guido, Guido Costa, Fabio Procopio, Luca Viganó, and Matteo Donadon. "Intraoperative Evaluation of Resectability." In Extreme Hepatic Surgery and Other Strategies. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-13896-1_11.
Texto completoSzadkowski, Rudolf, Jan Drchal, and Jan Faigl. "Basic Evaluation Scenarios for Incrementally Trained Classifiers." In Lecture Notes in Computer Science. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30484-3_41.
Texto completoViechnicki, Peter. "A performance evaluation of automatic survey classifiers." In Grammatical Inference. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0054080.
Texto completoCieslak, Kasia P., Roelof J. Bennink, and Thomas M. van Gulik. "Preoperative Evaluation of Liver Function." In Extreme Hepatic Surgery and Other Strategies. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-13896-1_3.
Texto completoChao, J. Carlos Aguado. "Artificial Intelligence Classifiers and Their Social Impact." In Soft Computing for Risk Evaluation and Management. Physica-Verlag HD, 2001. http://dx.doi.org/10.1007/978-3-7908-1814-7_11.
Texto completoNirkhi, Smita. "Evaluation of Classifiers for Detection of Authorship Attribution." In Computational Intelligence: Theories, Applications and Future Directions - Volume I. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1132-1_18.
Texto completoActas de conferencias sobre el tema "Evaluation of extreme classifiers"
Ostapuk, Natalia, Ljiljana Dolamic, Alain Mermoud, and Philippe Cudré-Mauroux. "Leveraging Pre-Trained Extreme Multi-Label Classifiers for Zero-Shot Learning." In 2024 11th IEEE Swiss Conference on Data Science (SDS). IEEE, 2024. http://dx.doi.org/10.1109/sds60720.2024.00041.
Texto completoKostko, Oleg, Maximillian Mueller, and Patrick Naulleau. "Electron blur evaluation for different electron energies." In International Conference on Extreme Ultraviolet Lithography 2024, edited by Joern-Holger Franke, Kurt G. Ronse, Paolo A. Gargini, Patrick P. Naulleau, and Toshiro Itani. SPIE, 2024. http://dx.doi.org/10.1117/12.3034739.
Texto completoHamdan, S., S. Wagle, S. Poudel, Y. Zhou, and K. Poudel. "Assessing Algorithmic Bias in Machine Learning Classifiers: A Fairness Evaluation." In 2024 IEEE Signal Processing in Medicine and Biology Symposium (SPMB). IEEE, 2024. https://doi.org/10.1109/spmb62441.2024.10842230.
Texto completoHosoda, Kazuki, Takashi Namikawa, Shinji Yamakawa, Tetsuo Harada, and Takeo Watanabe. "Outgas evaluation of cable materials for EUV lithography system." In International Conference on Extreme Ultraviolet Lithography 2024, edited by Joern-Holger Franke, Kurt G. Ronse, Paolo A. Gargini, Patrick P. Naulleau, and Toshiro Itani. SPIE, 2024. http://dx.doi.org/10.1117/12.3033877.
Texto completoBritto, Larissa, and Luciano Pacífico. "Classificação de Espécies de Plantas Usando Extreme Learning Machine." In Encontro Nacional de Inteligência Artificial e Computacional. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/eniac.2019.9268.
Texto completoFlores, Christian, Christian Fonseca, David Achanccaray, and Javier Andreu-Perez. "Performance Evaluation of a P300 Brain-Computer Interface Using a Kernel Extreme Learning Machine Classifier." In 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2018. http://dx.doi.org/10.1109/smc.2018.00629.
Texto completoItikawa, M. A., V. R. R. Ahón, T. A. Souza, et al. "Automatic Cement Evaluation Using Machine Learning." In Offshore Technology Conference Brasil. OTC, 2023. http://dx.doi.org/10.4043/32961-ms.
Texto completoGautam, Chandan, Aruna Tiwari, and Sriram Ravindran. "Construction of multi-class classifiers by Extreme Learning Machine based one-class classifiers." In 2016 International Joint Conference on Neural Networks (IJCNN). IEEE, 2016. http://dx.doi.org/10.1109/ijcnn.2016.7727445.
Texto completoFein-Ashley, Jacob, Tian Ye, Rajgopal Kannan, Viktor Prasanna, and Carl Busart. "Benchmarking Deep Learning Classifiers for SAR Automatic Target Recognition." In 2023 IEEE High Performance Extreme Computing Conference (HPEC). IEEE, 2023. http://dx.doi.org/10.1109/hpec58863.2023.10363455.
Texto completoSivaguru, Raaghavi, Chhaya Choudhary, Bin Yu, Vadym Tymchenko, Anderson Nascimento, and Martine De Cock. "An Evaluation of DGA Classifiers." In 2018 IEEE International Conference on Big Data (Big Data). IEEE, 2018. http://dx.doi.org/10.1109/bigdata.2018.8621875.
Texto completoInformes sobre el tema "Evaluation of extreme classifiers"
KAB LABS INC SAN DIEGO CA. Feature Set Evaluation for Classifiers. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada226903.
Texto completoKAB LABS INC SAN DIEGO CA. Feature Set Evaluation for Classifiers. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada226905.
Texto completoLiguori, Giovanni, and Nadia Pinardi. Evaluation of Extreme Forecast Indices (WP5+6). EuroSea, 2023. http://dx.doi.org/10.3289/eurosea_d4.11.
Texto completoAsenath-Smith, Emily, Terry Melendy, Amelia Menke, Andrew Bernier, and George Blaisdell. Evaluation of airfield damage repair methods for extreme cold temperatures. Engineer Research and Development Center (U.S.), 2019. http://dx.doi.org/10.21079/11681/32298.
Texto completoRuby, Brent C. Evaluation of the Human/Extreme Environment Interaction: Implications for Enhancing Operational Performance and Recovery. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada592672.
Texto completoRuby, Brent C. Evaluation of the Human/Extreme Environment Interaction: Implications for Enhancing Operational Performance and Recovery. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada592673.
Texto completoRuby, Brent C. Evaluation of the Human/Extreme Environment Interaction: Implications for Enhancing Operational Performance and Recovery. Defense Technical Information Center, 2014. http://dx.doi.org/10.21236/ada600954.
Texto completoBäumler, Maximilian, and Matthias Lehmann. Generating representative test scenarios: The FUSE for Representativity (fuse4rep) process model for collecting and analysing traffic observation data. TU Dresden, 2024. http://dx.doi.org/10.26128/2024.2.
Texto completoTruffer-Moudra, Dana, Sarah Azmi-Wendler, Robbin Garber-Slaght, Prateek Shrestha, Qwerty Mackey, and Conor Dennehy. Performance Evaluation and Costs of a Combined Ground Source Heat Pump and Solar Photovoltaic Storage System in an Extreme Cold Climate. Office of Scientific and Technical Information (OSTI), 2023. http://dx.doi.org/10.2172/1986504.
Texto completoHuntington, Dale. Anti-trafficking programs in South Asia: Appropriate activities, indicators and evaluation methodologies. Population Council, 2002. http://dx.doi.org/10.31899/rh2002.1019.
Texto completo