Literatura académica sobre el tema "Data Subgroup"
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 "Data Subgroup".
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 "Data Subgroup"
Kavšek, Branko y Nada Lavrač. "Using subgroup discovery to analyze the UK traffic data". Advances in Methodology and Statistics 1, n.º 1 (1 de enero de 2004): 249–64. http://dx.doi.org/10.51936/zewh2294.
Texto completoHuang, Xifen, Chaosong Xiong, Jinfeng Xu, Jianhua Shi y Jinhong Huang. "Mixture Modeling of Time-to-Event Data in the Proportional Odds Model". Mathematics 10, n.º 18 (16 de septiembre de 2022): 3375. http://dx.doi.org/10.3390/math10183375.
Texto completoMukherjee, Shubhabrata, Jesse Mez, Emily H. Trittschuh, Andrew J. Saykin, Laura E. Gibbons, David W. Fardo, Madeline Wessels et al. "Genetic data and cognitively defined late-onset Alzheimer’s disease subgroups". Molecular Psychiatry 25, n.º 11 (4 de diciembre de 2018): 2942–51. http://dx.doi.org/10.1038/s41380-018-0298-8.
Texto completoLötsch, Jörn y Alfred Ultsch. "Current Projection Methods-Induced Biases at Subgroup Detection for Machine-Learning Based Data-Analysis of Biomedical Data". International Journal of Molecular Sciences 21, n.º 1 (20 de diciembre de 2019): 79. http://dx.doi.org/10.3390/ijms21010079.
Texto completoEmery, William. "WOCE/TOGA Historical Oceanographic Data Subgroup". Eos, Transactions American Geophysical Union 67, n.º 22 (1986): 500. http://dx.doi.org/10.1029/eo067i022p00500-03.
Texto completoPan, Yunzhi, Weidan Pu, Xudong Chen, Xiaojun Huang, Yan Cai, Haojuan Tao, Zhiming Xue et al. "Morphological Profiling of Schizophrenia: Cluster Analysis of MRI-Based Cortical Thickness Data". Schizophrenia Bulletin 46, n.º 3 (4 de enero de 2020): 623–32. http://dx.doi.org/10.1093/schbul/sbz112.
Texto completoShirrell, Matthew. "The Effects of Subgroup-Specific Accountability on Teacher Turnover and Attrition". Education Finance and Policy 13, n.º 3 (julio de 2018): 333–68. http://dx.doi.org/10.1162/edfp_a_00227.
Texto completoKoopman, Laura, Geert J. M. G. van der Heijden, Arno W. Hoes, Diederick E. Grobbee y Maroeska M. Rovers. "Empirical comparison of subgroup effects in conventional and individual patient data meta-analyses". International Journal of Technology Assessment in Health Care 24, n.º 03 (julio de 2008): 358–61. http://dx.doi.org/10.1017/s0266462308080471.
Texto completoNanlin Jin, Peter Flach, Tom Wilcox, Royston Sellman, Joshua Thumim y Arno Knobbe. "Subgroup Discovery in Smart Electricity Meter Data". IEEE Transactions on Industrial Informatics 10, n.º 2 (mayo de 2014): 1327–36. http://dx.doi.org/10.1109/tii.2014.2311968.
Texto completoTsai, Kao-Tai y Karl Peace. "Analysis of Subgroup Data of Clinical Trials". Journal of Causal Inference 1, n.º 2 (10 de septiembre de 2013): 193–207. http://dx.doi.org/10.1515/jci-2012-0008.
Texto completoTesis sobre el tema "Data Subgroup"
Atzmüller, Martin. "Knowledge-intensive subgroup mining : techniques for automatic and interactive discovery /". Berlin : Aka, 2007. http://deposit.d-nb.de/cgi-bin/dokserv?id=2928288&prov=M&dok_var=1&dok_ext=htm.
Texto completoAtzmüller, Martin. "Knowledge-intensive subgroup mining techniques for automatic and interactive discovery". Berlin Aka, 2006. http://deposit.d-nb.de/cgi-bin/dokserv?id=2928288&prov=M&dok_var=1&dok_ext=htm.
Texto completoBelfodil, Aimene. "An order theoretic point-of-view on subgroup discovery". Thesis, Lyon, 2019. http://www.theses.fr/2019LYSEI078.
Texto completoAs the title of this dissertation may suggest, the aim of this thesis is to provide an order-theoretic point of view on the task of subgroup discovery. Subgroup discovery is the automatic task of discovering interesting hypotheses in databases. That is, given a database, the hypothesis space the analyst wants to explore and a formal way of how the analyst gauges the quality of the hypotheses (e.g. a quality measure); the automated task of subgroup discovery aims to extract the interesting hypothesis w.r.t. these parameters. In order to elaborate fast and efficient algorithms for subgroup discovery, one should understand the underlying properties of the hypothesis space on the one hand and the properties of its quality measure on the other. In this thesis, we extend the state-of-the-art by: (i) providing a unified view of the hypotheses space behind subgroup discovery using the well-founded mathematical tool of order theory, (ii) proposing the new hypothesis space of conjunction of linear inequalities in numerical databases and the algorithms enumerating its elements and (iii) proposing an anytime algorithm for discriminative subgroup discovery on numerical datasets providing guarantees upon interruption
Mistry, Dipesh. "Recursive partitioning based approaches for low back pain subgroup identification in individual patient data meta-analyses". Thesis, University of Warwick, 2014. http://wrap.warwick.ac.uk/64032/.
Texto completoDoubleday, Kevin. "Generation of Individualized Treatment Decision Tree Algorithm with Application to Randomized Control Trials and Electronic Medical Record Data". Thesis, The University of Arizona, 2016. http://hdl.handle.net/10150/613559.
Texto completoMueller, Marianne Larissa [Verfasser], Stefan [Akademischer Betreuer] Kramer y Frank [Akademischer Betreuer] Puppe. "Data Mining Methods for Medical Diagnosis : Test Selection, Subgroup Discovery, and Contrained Clustering / Marianne Larissa Mueller. Gutachter: Stefan Kramer ; Frank Puppe. Betreuer: Stefan Kramer". München : Universitätsbibliothek der TU München, 2012. http://d-nb.info/1024964264/34.
Texto completoLi, Rui [Verfasser], Burkhard [Akademischer Betreuer] [Gutachter] Rost y Stefan [Gutachter] Kramer. "Data Mining and Machine Learning Methods for High-dimensional Patient Data in Dementia Research: Voxel Features Mining, Subgroup Discovery and Multi-view Learning / Rui Li ; Gutachter: Burkhard Rost, Stefan Kramer ; Betreuer: Burkhard Rost". München : Universitätsbibliothek der TU München, 2017. http://d-nb.info/1125018224/34.
Texto completoDomingue, Jean-Laurent. "Nurses’ Knowledge, Attitudes and Documentation Practices in a Context of HIV Criminalization: A Secondary Subgroup Analysis of Data from California, Florida, New York, and Texas Nurses". Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/35570.
Texto completoBelfodil, Adnene. "Exceptional model mining for behavioral data analysis". Thesis, Lyon, 2019. http://www.theses.fr/2019LYSEI086.
Texto completoWith the rapid proliferation of data platforms collecting and curating data related to various domains such as governments data, education data, environment data or product ratings, more and more data are available online. This offers an unparalleled opportunity to study the behavior of individuals and the interactions between them. In the political sphere, being able to query datasets of voting records provides interesting insights for data journalists and political analysts. In particular, such data can be leveraged for the investigation of exceptionally consensual/controversial topics. Consider data describing the voting behavior in the European Parliament (EP). Such a dataset records the votes of each member (MEP) in voting sessions held in the parliament, as well as information on the parliamentarians (e.g., gender, national party, European party alliance) and the sessions (e.g., topic, date). This dataset offers opportunities to study the agreement or disagreement of coherent subgroups, especially to highlight unexpected behavior. It is to be expected that on the majority of voting sessions, MEPs will vote along the lines of their European party alliance. However, when matters are of interest to a specific nation within Europe, alignments may change and agreements can be formed or dissolved. For instance, when a legislative procedure on fishing rights is put before the MEPs, the island nation of the UK can be expected to agree on a specific course of action regardless of their party alliance, fostering an exceptional agreement where strong polarization exists otherwise. In this thesis, we aim to discover such exceptional (dis)agreement patterns not only in voting data but also in more generic data, called behavioral data, which involves individuals performing observable actions on entities. We devise two novel methods which offer complementary angles of exceptional (dis)agreement in behavioral data: within and between groups. These two approaches called Debunk and Deviant, ideally, enables the implementation of a sufficiently comprehensive tool to highlight, summarize and analyze exceptional comportments in behavioral data. We thoroughly investigate the qualitative and quantitative performances of the devised methods. Furthermore, we motivate their usage in the context of computational journalism
Wesley, S. Scott. "Background data subgroups and career outcomes : some developmental influences on person job-matching". Diss., Georgia Institute of Technology, 1989. http://hdl.handle.net/1853/31065.
Texto completoLibros sobre el tema "Data Subgroup"
Atzmüller, Martin. Knowledge-intensive subgroup mining: Techniques for automatic and interactive discovery. Berlin: Aka, Akademische Verlagsgsellschaft, 2007.
Buscar texto completoOffice, General Accounting. Decennial census: Methods for collecting and reporting Hispanic subgroup data need refinement : report to Congressional Requesters. [Washington, D.C.]: GAO, 2003.
Buscar texto completoSiek-Toon, Khoo, Goff Ginger Nelson y Educational Resources Information Center (U.S.), eds. Multidimensional description of subgroup differences in mathematics achievement data from the 1992 National Assessment of Educational Progress: Draft. Los Angeles CA: National Center for Research on Evaluation, Standards, and Student Testing, 1994.
Buscar texto completoWright, Thomas L. Chemical data for flows and feeder dikes of the Yakima Basalt Subgroup, Columbia River Basalt Group, Washington, Oregon, and Idaho, and their bearing on a petrogenetic model. Washington: U.S. G.P.O., 1989.
Buscar texto completo1932-, Kameny Iris, United States. Defense Modeling and Simulation Office. Data and Repositories Technology Working Group., National Defense Research Institute (U.S.) y United States. Dept. of Defense., eds. Defense Modeling and Simulation Office Data and Repositories Technology Working Group (DRTWG) meetings held February 7-10, 1995, and additional task force and subgroup meetings held between July 1994 and February 1995. Santa Monica, CA: Rand, 1995.
Buscar texto completoHajat, Anjum. Health outcomes among Hispanic subgroups: Data from the National Health Interview Survey, 1992-95. [Hyattsville, Md.] (6525 Belcrest Rd., Hyattsville 20782-2003): [U.S. Dept. of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics, 2000.
Buscar texto completoUnited States. Substance Abuse and Mental Health Services Administration. Office of Applied Studies., ed. Prevalence of substance use among racial and ethnic subgroups in the United States, 1991-1993. Rockville, Md. (5600 Fishers Lane, Rm. 16-105, Rockville 20857): Dept. of Health and Human Services, Substance Abuse and Mental Health Services Administration, Office of Applied Studies, 1998.
Buscar texto completoAtzmuller, Martin. Knowledge-Intensive Subgroup Mining: Techniques for Automatic and Interactive Discovery - Volume 307 Dissertations in Artificial Intelligence - Infix ... in Artificial Intelligence). IOS Press, 2007.
Buscar texto completoTran, Thanh V. y Keith T. Chan. Applied Cross-Cultural Data Analysis for Social Work. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780190888510.001.0001.
Texto completoProctor, Kim. Measuring Group Consciousness. Editado por Lonna Rae Atkeson y R. Michael Alvarez. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780190213299.013.33.
Texto completoCapítulos de libros sobre el tema "Data Subgroup"
Cleophas, Ton J. y Aeilko H. Zwinderman. "Subgroup Analysis". En Understanding Clinical Data Analysis, 141–56. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39586-9_7.
Texto completoKlösgen, W. "Subgroup Mining". En Computational Intelligence in Data Mining, 39–49. Vienna: Springer Vienna, 2000. http://dx.doi.org/10.1007/978-3-7091-2588-5_2.
Texto completoKim, Ju Han. "Gene Set Approaches and Prognostic Subgroup Prediction". En Genome Data Analysis, 135–57. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-1942-6_8.
Texto completoLavrač, Nada. "Subgroup Discovery Techniques and Applications". En Advances in Knowledge Discovery and Data Mining, 2–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11430919_2.
Texto completoAtzmueller, Martin, Juergen Mueller y Martin Becker. "Exploratory Subgroup Analytics on Ubiquitous Data". En Lecture Notes in Computer Science, 1–20. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-14723-9_1.
Texto completoGähler, Franz. "Computer checking of the subgroup data". En International Tables for Crystallography, 27–28. Chester, England: International Union of Crystallography, 2006. http://dx.doi.org/10.1107/97809553602060000540.
Texto completoGähler, Franz. "Computer checking of the subgroup data". En International Tables for Crystallography, 25–26. Chester, England: International Union of Crystallography, 2011. http://dx.doi.org/10.1107/97809553602060000792.
Texto completoDzyuba, Vladimir y Matthijs van Leeuwen. "Interactive Discovery of Interesting Subgroup Sets". En Advances in Intelligent Data Analysis XII, 150–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41398-8_14.
Texto completoMillot, Alexandre, Rémy Cazabet y Jean-François Boulicaut. "Optimal Subgroup Discovery in Purely Numerical Data". En Advances in Knowledge Discovery and Data Mining, 112–24. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-47436-2_9.
Texto completoCleophas, Ton J. y Aeilko H. Zwinderman. "Subgroup Characteristics Assessed as Dependent Adverse Effects". En Analysis of Safety Data of Drug Trials, 183–93. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-05804-3_14.
Texto completoActas de conferencias sobre el tema "Data Subgroup"
Lemmerich, Florian y Frank Puppe. "Local Models for Expectation-Driven Subgroup Discovery". En 2011 IEEE 11th International Conference on Data Mining (ICDM). IEEE, 2011. http://dx.doi.org/10.1109/icdm.2011.94.
Texto completoYang, Xi, Yuan Zhang y Min Chi. "Time-aware Subgroup Matrix Decomposition: Imputing Missing Data Using Forecasting Events". En 2018 IEEE International Conference on Big Data (Big Data). IEEE, 2018. http://dx.doi.org/10.1109/bigdata.2018.8622436.
Texto completoLiu, Jing, Yu Jiang, Zechao Li, Xi Zhang y Hanqing Lu. "Domain-sensitive Recommendation with user-item subgroup analysis". En 2016 IEEE 32nd International Conference on Data Engineering (ICDE). IEEE, 2016. http://dx.doi.org/10.1109/icde.2016.7498377.
Texto completoLijffijt, Jefrey, Bo Kang, Wouter Duivesteijn, Kai Puolamaki, Emilia Oikarinen y Tijl De Bie. "Subjectively Interesting Subgroup Discovery on Real-Valued Targets". En 2018 IEEE 34th International Conference on Data Engineering (ICDE). IEEE, 2018. http://dx.doi.org/10.1109/icde.2018.00148.
Texto completoMathonat, Romain, Diana Nurbakova, Jean-Francois Boulicaut y Mehdi Kaytoue. "Anytime Subgroup Discovery in High Dimensional Numerical Data". En 2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA). IEEE, 2021. http://dx.doi.org/10.1109/dsaa53316.2021.9564223.
Texto completoTrabold, Daniel y Henrik Grosskreutz. "Parallel subgroup discovery on computing clusters — First results". En 2013 IEEE International Conference on Big Data. IEEE, 2013. http://dx.doi.org/10.1109/bigdata.2013.6691625.
Texto completoPurucker, Lennart, Felix Stamm, Florian Lemmerich y Joeran Beel. "Estimating the Pruned Search Space Size of Subgroup Discovery". En 2022 IEEE International Conference on Data Mining (ICDM). IEEE, 2022. http://dx.doi.org/10.1109/icdm54844.2022.00147.
Texto completoPadillo, F., J. M. Luna y S. Ventura. "Subgroup discovery on big data: Pruning the search space on exhaustive search algorithms". En 2016 IEEE International Conference on Big Data (Big Data). IEEE, 2016. http://dx.doi.org/10.1109/bigdata.2016.7840799.
Texto completoMeeng, Marvin, Wouter Duivesteijn y Arno Knobbe. "ROCsearch — An ROC-guided Search Strategy for Subgroup Discovery". En Proceedings of the 2014 SIAM International Conference on Data Mining. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2014. http://dx.doi.org/10.1137/1.9781611973440.81.
Texto completoShukla, Piyush Kumar, Pradeep Rusiya, Deepak Agrawal, Lata Chhablani y Balwant Singh Raghuwanshi. "Multiple Subgroup Data Compression Technique Based on Huffman Coding". En 2009 First International Conference on Computational Intelligence, Communication Systems and Networks (CICSYN). IEEE, 2009. http://dx.doi.org/10.1109/cicsyn.2009.86.
Texto completoInformes sobre el tema "Data Subgroup"
Kim, Kang Seog. SUBGR: A Program to Generate Subgroup Data for the Subgroup Resonance Self-Shielding Calculation. Office of Scientific and Technical Information (OSTI), junio de 2016. http://dx.doi.org/10.2172/1261346.
Texto completoWu, Ling, Tao Zhang, Yao Wang, Xiao Ke Wu, Tin Chiu Li, Pui Wah Chung y Chi Chiu Wang. Polymorphisms and premature ovarian insufficiency and failure: A comprehensive meta-analysis update, subgroup, ranking, and network analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, enero de 2022. http://dx.doi.org/10.37766/inplasy2022.1.0052.
Texto completoWells, Aaron, Tracy Christopherson, Gerald Frost, Matthew Macander, Susan Ives, Robert McNown y Erin Johnson. Ecological land survey and soils inventory for Katmai National Park and Preserve, 2016–2017. National Park Service, septiembre de 2021. http://dx.doi.org/10.36967/nrr-2287466.
Texto completoCaulfield, Laura E., Wendy L. Bennett, Susan M. Gross, Kristen M. Hurley, S. Michelle Ogunwole, Maya Venkataramani, Jennifer L. Lerman, Allen Zhang, Ritu Sharma y Eric B. Bass. Maternal and Child Outcomes Associated With the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). Agency for Healthcare Research and Quality (AHRQ), abril de 2022. http://dx.doi.org/10.23970/ahrqepccer253.
Texto completoChou, Roger, Rongwei Fu, Tracy Dana, Miranda Pappas, Erica Hart y Kimberly M. Mauer. Interventional Treatments for Acute and Chronic Pain: Systematic Review. Agency for Healthcare Research and Quality (AHRQ), septiembre de 2021. http://dx.doi.org/10.23970/ahrqepccer247.
Texto completoSpitzer, Sonja, Vanessa di Lego, Angela Greulich y Raya Muttarak. A demographic perspective on human wellbeing: Concepts, measurement and population heterogeneity. Verlag der Österreichischen Akademie der Wissenschaften, septiembre de 2021. http://dx.doi.org/10.1553/populationyearbook2021.int01.
Texto completoChou, Roger, Jesse Wagner, Azrah Y. Ahmed, Ian Blazina, Erika Brodt, David I. Buckley, Tamara P. Cheney et al. Treatments for Acute Pain: A Systematic Review. Agency for Healthcare Research and Quality (AHRQ), diciembre de 2020. http://dx.doi.org/10.23970/ahrqepccer240.
Texto completoWu, Bin, Lixia Guo, Kaikai Zhen y Chao Sun. Diagnostic and prognostic value of miRNAs in hepatoblastoma: A systematic review with meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, noviembre de 2021. http://dx.doi.org/10.37766/inplasy2021.11.0045.
Texto completoShumway, Dean A., Kimberly S. Corbin, Magdoleen H. Farah, Kelly E. Viola, Tarek Nayfeh, Samer Saadi, Vishal Shah et al. Partial Breast Irradiation for Breast Cancer. Agency for Healthcare Research and Quality (AHRQ), enero de 2023. http://dx.doi.org/10.23970/ahrqepccer259.
Texto completoMobley, Erin M., Diana J. Moke, Joel Milam, Carol Y. Ochoa, Julia Stal, Nosa Osazuwa, Maria Bolshakova et al. Disparities and Barriers to Pediatric Cancer Survivorship Care. Agency for Healthcare Research and Quality (AHRQ), marzo de 2021. http://dx.doi.org/10.23970/ahrqepctb39.
Texto completo