Literatura académica sobre el tema "Auc-Roc"
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Artículos de revistas sobre el tema "Auc-Roc"
Hong, Chong Sun y So Yeon Choi. "ROC curve generalization and AUC". Journal of the Korean Data And Information Science Society 31, n.º 4 (31 de julio de 2020): 477–88. http://dx.doi.org/10.7465/jkdi.2020.31.4.477.
Texto completoHong, Chong Sun y Dae Soon Yang. "ROC curve and AUC for linear growth models". Journal of the Korean Data and Information Science Society 26, n.º 6 (30 de noviembre de 2015): 1367–75. http://dx.doi.org/10.7465/jkdi.2015.26.6.1367.
Texto completoМинин, А. С. "Бинаризация вероятностного прогноза методом ROC AUC". ТЕНДЕНЦИИ РАЗВИТИЯ НАУКИ И ОБРАЗОВАНИЯ 104, n.º 14 (2023): 87–91. http://dx.doi.org/10.18411/trnio-12-2023-789.
Texto completoKrupinski, Elizabeth A. "Evaluating AI Clinically—It’s Not Just ROC AUC!" Radiology 298, n.º 1 (enero de 2021): 47–48. http://dx.doi.org/10.1148/radiol.2020203782.
Texto completoMukhametshin, Rustam F., Olga P. Kovtun y Nadezhda S. Davydova. "Respiratory parameters as a predictor of hospital outcomes in newborns requiring medical evacuation". Russian Journal of Pediatric Surgery, Anesthesia and Intensive Care 12, n.º 4 (19 de enero de 2023): 441–52. http://dx.doi.org/10.17816/psaic1292.
Texto completoMuschelli, John. "ROC and AUC with a Binary Predictor: a Potentially Misleading Metric". Journal of Classification 37, n.º 3 (23 de diciembre de 2019): 696–708. http://dx.doi.org/10.1007/s00357-019-09345-1.
Texto completoKhaidarov, A. G., A. I. Soloviev y D. A. Budko. "STUDY OF THE MOST EFFICIENT MODELS AND ATRIBUTION ALGORITHMS USING THE ROC AUC INDICATOR". Современные наукоемкие технологии (Modern High Technologies), n.º 7 2022 (2022): 63–68. http://dx.doi.org/10.17513/snt.39234.
Texto completoGarcía de Guadiana-Romualdo, Luis, María Dolores Albaladejo-Otón, Mario Berger, Enrique Jiménez-Santos, Roberto Jiménez-Sánchez, Patricia Esteban-Torrella, Sergio Rebollo-Acebes, Ana Hernando-Holgado, Alejandro Ortín-Freire y Javier Trujillo-Santos. "Prognostic performance of pancreatic stone protein in critically ill patients with sepsis". Biomarkers in Medicine 13, n.º 17 (diciembre de 2019): 1469–80. http://dx.doi.org/10.2217/bmm-2019-0174.
Texto completoSauka, Kudzai, Gun-Yoo Shin, Dong-Wook Kim y Myung-Mook Han. "Adversarial Robust and Explainable Network Intrusion Detection Systems Based on Deep Learning". Applied Sciences 12, n.º 13 (25 de junio de 2022): 6451. http://dx.doi.org/10.3390/app12136451.
Texto completoAmala, R. y Sudesh Pundir. "ROC Curve and AUC for A Left-Truncated Sample from Rayleigh Distribution". American Journal of Mathematical and Management Sciences 34, n.º 2 (31 de diciembre de 2014): 89–116. http://dx.doi.org/10.1080/01966324.2014.969461.
Texto completoTesis sobre el tema "Auc-Roc"
Zheng, Shimin. "The ROC Curve and the Area under the Curve (AUC)". Digital Commons @ East Tennessee State University, 2017. https://dc.etsu.edu/etsu-works/139.
Texto completoLu, Qing. "Methods for Designing and Forming Predictive Genetic Tests". Case Western Reserve University School of Graduate Studies / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=case1212197560.
Texto completoYuan, Yan. "Empirical Likelihood-Based NonParametric Inference for the Difference between Two Partial AUCS". Digital Archive @ GSU, 2007. http://digitalarchive.gsu.edu/math_theses/32.
Texto completoHuang, Xin. "Bootstrap and Empirical Likelihood-based Semi-parametric Inference for the Difference between Two Partial AUCs". Digital Archive @ GSU, 2008. http://digitalarchive.gsu.edu/math_theses/54.
Texto completoSun, Fangfang. "Semi-parametric inference for the partial area under the ROC curve". unrestricted, 2008. http://etd.gsu.edu/theses/available/etd-11192008-113213/.
Texto completoTitle from file title page. Gengsheng Qin, committee chair; Yu-Sheng Hsu, Yixin Fang, Yuanhui Xiao, committee members. Description based on contents viewed July 22, 2009. Includes bibliographical references (p. 29-30).
Zhou, Haochuan. "Statistical Inferences for the Youden Index". Digital Archive @ GSU, 2011. http://digitalarchive.gsu.edu/math_diss/5.
Texto completoXu, Ping. "Evaluation of Repeated Biomarkers: Non-parametric Comparison of Areas under the Receiver Operating Curve Between Correlated Groups Using an Optimal Weighting Scheme". Scholar Commons, 2012. http://scholarcommons.usf.edu/etd/4261.
Texto completoBitara, Matúš. "Srovnání heuristických a konvenčních statistických metod v data miningu". Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2019. http://www.nusl.cz/ntk/nusl-400833.
Texto completoKhamesipour, Alireza. "IMPROVED GENE PAIR BIOMARKERS FOR MICROARRAY DATA CLASSIFICATION". OpenSIUC, 2018. https://opensiuc.lib.siu.edu/dissertations/1573.
Texto completoWang, Binhuan. "Statistical Evaluation of Continuous-Scale Diagnostic Tests with Missing Data". Digital Archive @ GSU, 2012. http://digitalarchive.gsu.edu/math_diss/8.
Texto completoCapítulos de libros sobre el tema "Auc-Roc"
Klawonn, Frank, Frank Höppner y Sigrun May. "An Alternative to ROC and AUC Analysis of Classifiers". En Advances in Intelligent Data Analysis X, 210–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24800-9_21.
Texto completoGentili, Elisabetta, Alice Bizzarri, Damiano Azzolini, Riccardo Zese y Fabrizio Riguzzi. "Regularization in Probabilistic Inductive Logic Programming". En Inductive Logic Programming, 16–29. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-49299-0_2.
Texto completoMarcus, Pamela M. "Performance Measures". En Assessment of Cancer Screening, 23–38. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94577-0_3.
Texto completoKoncar, Philipp y Denis Helic. "Employee Satisfaction in Online Reviews". En Lecture Notes in Computer Science, 152–67. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60975-7_12.
Texto completoFeretzakis, Georgios, Aikaterini Sakagianni, Evangelos Loupelis, Dimitris Kalles, Vasileios Panteris, Lazaros Tzelves, Rea Chatzikyriakou et al. "Prediction of Hospitalization Using Machine Learning for Emergency Department Patients". En Studies in Health Technology and Informatics. IOS Press, 2022. http://dx.doi.org/10.3233/shti220422.
Texto completoKyparissidis Kokkinidis, Ilias, Evangelos Logaras, Emmanouil S. Rigas, Ioannis Tsakiridis, Themistoklis Dagklis, Antonis Billis y Panagiotis D. Bamidis. "Towards an Explainable AI-Based Tool to Predict Preterm Birth". En Caring is Sharing – Exploiting the Value in Data for Health and Innovation. IOS Press, 2023. http://dx.doi.org/10.3233/shti230207.
Texto completoSakagianni, Aikaterini, Christina Koufopoulou, Vassilios Verykios, Evangelos Loupelis, Dimitrios Kalles y Georgios Feretzakis. "Prediction of COVID-19 Mortality in the Intensive Care Unit Using Machine Learning". En Caring is Sharing – Exploiting the Value in Data for Health and Innovation. IOS Press, 2023. http://dx.doi.org/10.3233/shti230200.
Texto completoLakshmi Shree K. y Ashok Kumar R. "Global Events to Enhance Tourism". En Advances in Marketing, Customer Relationship Management, and E-Services, 66–86. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-6684-6591-2.ch005.
Texto completoSweetnich, Stephen R. y David R. Jacques. "Skin Detection With Small Unmanned Aerial Systems by Integration of Area Scan Multispectral Imagers and Factors Affecting Their Design and Operation". En Unmanned Aerial Vehicles, 215–34. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8365-3.ch009.
Texto completoFigueirêdo, Ilan, Lílian Lefol Nani Guarieiro y Erick Giovani Sperandio Nascimento. "Multivariate Real Time Series Data Using Six Unsupervised Machine Learning Algorithms". En Anomaly Detection - Recent Advances, Issues and Challenges [Working Title]. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.94944.
Texto completoActas de conferencias sobre el tema "Auc-Roc"
Hong, Shenda, Cao Xiao, Trong Nghia Hoang, Tengfei Ma, Hongyan Li y Jimeng Sun. "RDPD: Rich Data Helps Poor Data via Imitation". En Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/817.
Texto completoShekter, Dylan H. y Frank W. Samuelson. "Efficiently calculating ROC curves, AUC, and uncertainty from 2AFC studies with finite samples". En Image Perception, Observer Performance, and Technology Assessment, editado por Frank W. Samuelson y Sian Taylor-Phillips. SPIE, 2020. http://dx.doi.org/10.1117/12.2550601.
Texto completoFerris, Michael H., Michael McLaughlin, Samuel Grieggs, Soundararajan Ezekiel, Erik Blasch, Mark Alford, Maria Cornacchia y Adnan Bubalo. "Using ROC curves and AUC to evaluate performance of no-reference image fusion metrics". En NAECON 2015 - IEEE National Aerospace and Electronics Conference. IEEE, 2015. http://dx.doi.org/10.1109/naecon.2015.7443034.
Texto completoChaves, Rubens Marques, André Luis Debiaso Rossi y Luís Paulo Faina Garcia. "A Financial Distress Prediction using a Non-stationary Dataset". En Encontro Nacional de Inteligência Artificial e Computacional. Sociedade Brasileira de Computação - SBC, 2023. http://dx.doi.org/10.5753/eniac.2023.234013.
Texto completoRodrigues, Gustavo y Diego Kreutz. "Modelo preditivo para classificação de risco de óbito de pacientes com COVID-19 utilizando dados abertos". En Simpósio Brasileiro de Computação Aplicada à Saúde. Sociedade Brasileira de Computação - SBC, 2022. http://dx.doi.org/10.5753/sbcas.2022.222494.
Texto completoCalheiros, José, Lucas Amorim, Lucas Lima y Marcelo Oliveira. "Os efeitos da utilização de atributos perinodulares na classificação de nódulos pulmonares". En Anais Principais do Simpósio Brasileiro de Computação Aplicada à Saúde. Sociedade Brasileira de Computação - SBC, 2020. http://dx.doi.org/10.5753/sbcas.2020.11510.
Texto completoYunisa, Regina y Freddy Haryanto. "Sensitivity and accuracy analysis of CT image in PRISM autocontouring using confusion matrix and ROC/AUC curve methods". En THE 5TH INTERNATIONAL CONFERENCE ON MATHEMATICS AND NATURAL SCIENCES. AIP Publishing LLC, 2015. http://dx.doi.org/10.1063/1.4930656.
Texto completoAlam, S., O. Olabiyi, O. Odejide y A. Annamalai. "Energy detector's performance evaluation in a relay based cognitive radio network: Area under the ROC curve (AUC) approach". En 2011 IEEE Globecom Workshops. IEEE, 2011. http://dx.doi.org/10.1109/glocomw.2011.6162466.
Texto completoAmagada, P. U. "An Inferable Machine Learning Approach for Reservoir Lithology Characterization Using Drilling Data". En SPE Annual Technical Conference and Exhibition. SPE, 2023. http://dx.doi.org/10.2118/217485-stu.
Texto completoF. Machado, Giovani, Luciana F. Almeida y Juan G. Lazo Lazo. "Técnicas de Aprendizado de Máquina para Previsão de Perdas Severas em Rochas Carbonáticas de Reservatórios Do Pré-Sal". En Congresso Brasileiro de Automática - 2020. sbabra, 2020. http://dx.doi.org/10.48011/asba.v2i1.1264.
Texto completoInformes sobre el tema "Auc-Roc"
Tayeb, Shahab. Taming the Data in the Internet of Vehicles. Mineta Transportation Institute, enero de 2022. http://dx.doi.org/10.31979/mti.2022.2014.
Texto completoChen, Xiaole, Peng Wang, Yunquan Luo, Yi-Yu Lu, Wenjun Zhou, Mengdie Yang, Jian Chen, Zhi-Qiang Meng y Shi-Bing Su. Therapeutic Efficacy Evaluation and Underlying Mechanisms Prediction of Jianpi Liqi Decoction for Hepatocellular Carcinoma. Science Repository, septiembre de 2021. http://dx.doi.org/10.31487/j.jso.2021.02.04.sup.
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