Littérature scientifique sur le sujet « Training set analysi »
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Articles de revues sur le sujet "Training set analysi"
Jumaniyazov, Anvarbek B. « PEDAGOGICAL ANALYSIS OF TRAINING IN PHYSICAL EDUCATION AND SPORTS MANAGEMENT ». CURRENT RESEARCH JOURNAL OF PEDAGOGICS 03, no 05 (1 mai 2022) : 1–10. http://dx.doi.org/10.37547/pedagogics-crjp-03-05-01.
Texte intégralKara, Gökhan, Ozan Hikmet Arıcan et Olgay Okşaş. « Analysis of the Effect of Electronic Chart Display and Information System Simulation Technologies in Maritime Education ». Marine Technology Society Journal 54, no 3 (1 mai 2020) : 43–57. http://dx.doi.org/10.4031/mtsj.54.3.6.
Texte intégralWang, Jianzhong. « Mathematical analysis on out-of-sample extensions ». International Journal of Wavelets, Multiresolution and Information Processing 16, no 05 (septembre 2018) : 1850042. http://dx.doi.org/10.1142/s021969131850042x.
Texte intégralPattnaik, Saumendra, et Binod Kumar Pattanayak. « Empirical analysis of software quality prediction using a TRAINBFG algorithm ». International Journal of Engineering & ; Technology 7, no 2.6 (11 mars 2018) : 259. http://dx.doi.org/10.14419/ijet.v7i2.6.10780.
Texte intégralKING, FOO SHOU, P. SARATCHANDRAN et N. SUNDARARAJAN. « ANALYSIS OF TRAINING SET PARALLELISM FOR BACKPROPAGATION NEURAL NETWORKS ». International Journal of Neural Systems 06, no 01 (mars 1995) : 61–78. http://dx.doi.org/10.1142/s0129065795000068.
Texte intégralAliyuda, Kachalla, et John Howell. « Machine-learning algorithm for estimating oil-recovery factor using a combination of engineering and stratigraphic dependent parameters ». Interpretation 7, no 3 (1 août 2019) : SE151—SE159. http://dx.doi.org/10.1190/int-2018-0211.1.
Texte intégralCohen, Albert, Wolfgang Dahmen, Ronald DeVore et James Nichols. « Reduced Basis Greedy Selection Using Random Training Sets ». ESAIM : Mathematical Modelling and Numerical Analysis 54, no 5 (16 juillet 2020) : 1509–24. http://dx.doi.org/10.1051/m2an/2020004.
Texte intégralEmbros, Grzegorz. « Audyt zachowań jako narzędzie systemu zarządzania bezpieczeństwem i higieną pracy ». Studia Ecologiae et Bioethicae 7, no 1 (30 juin 2009) : 165–79. http://dx.doi.org/10.21697/seb.2009.7.1.11.
Texte intégralNúñez, Sergio, Daniel Borrajo et Carlos Linares López. « Performance Analysis of Planning Portfolios ». Proceedings of the International Symposium on Combinatorial Search 3, no 1 (20 août 2021) : 65–71. http://dx.doi.org/10.1609/socs.v3i1.18238.
Texte intégralKozma, Gábor Viktor. « Actor Training as a Method of Directors. Training in Context of the Odin Teatret’s Creative Work and Higher Education ». Studia Universitatis Babeş-Bolyai Dramatica 67, no 2 (13 décembre 2022) : 29–45. http://dx.doi.org/10.24193/subbdrama.2022.2.02.
Texte intégralThèses sur le sujet "Training set analysi"
Demirel, Hasan. « Training set analysis for image-based facial feature detection ». Thesis, Imperial College London, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.264934.
Texte intégralGambel, Ray, David Lundy, William Murphy et Southmost Consulting. « Analysis of Transportation Alternatives for Ejection Seat Training ». Thesis, Monterey, California. Naval Postgraduate School, 2011. http://hdl.handle.net/10945/7068.
Texte intégralEXECUTIVE SUMMARY Student Military Aviators who complete primary flight training at Training Wing FOUR and select jets for their advanced training track will require Naval Aviation Survival Training Program (NASTP) Class 1 training until the T-6B replaces the T-34C as the primary flight training aircraft. This Class 1 training instructs students in ejection seat equipment and procedures for emergency egress of their new aircraft. Of the eight available Aviation Survival Training Centers (ASTC) Training Wing FOUR sends its students exclusively to NAS Pensacola. Training Wing FOUR utilizes a TC-12B training aircraft for the logistical transport of students to and from Class 1 training approximately twice weekly, called the DJET. CDR Christian Schomaker, Training Wing FOUR Operations Officer, commissioned this study to provide an analysis of alternatives to the current method of transporting students. RECOMMENDED OPTIONS A. Provide all flight students Class 1 training at ASTC Pensacola, Florida while in Pensacola as part of the Aviation Preflight Indoctrination (API) curriculum prior to permanent change of station to Corpus Christ, Texas. B. Adjust the DJET flight schedule to a Sunday departure rather than a Friday departure, resulting in a $209.00 savings per student of per diem cost which amounts to approximately $21,000.00 per fiscal year. C. Readdress current local restrictions and classification of student naval aviators as aircrew to enable multi-engine student flight training on DJET flights. D. Consider utilizing other ASTC facilities; specifically, aligning the Class 1 ejection seat training with the required Centrifuge-based Flight Environment Training (CFET) at ASTC Lemoore.
Wagle, John P., Aaron Cunanan, Kevin M. Carroll, Matt L. Sams, Alexander Wetmore, Garett E. Bingham, Christopher B. Taber et al. « Accentuated Eccentric Loading and Cluster Set Configurations in the Back Squat : A Kinetic and Kinematic Analysis ». Digital Commons @ East Tennessee State University, 2018. https://dc.etsu.edu/etsu-works/4666.
Texte intégralMyburgh, Gerhard. « The impact of training set size and feature dimensionality on supervised object-based classification : a comparison of three classifiers ». Thesis, Stellenbosch : Stellenbosch University, 2012. http://hdl.handle.net/10019.1/71655.
Texte intégralENGLISH ABSTRACT: Supervised classifiers are commonly used in remote sensing to extract land cover information. They are, however, limited in their ability to cost-effectively produce sufficiently accurate land cover maps. Various factors affect the accuracy of supervised classifiers. Notably, the number of available training samples is known to significantly influence classifier performance and to obtain a sufficient number of samples is not always practical. The support vector machine (SVM) does perform well with a limited number of training samples. But little research has been done to evaluate SVM’s performance for geographical object-based image analysis (GEOBIA). GEOBIA also allows the easy integration of additional features into the classification process, a factor which may significantly influence classification accuracies. As such, two experiments were developed and implemented in this research. The first compared the performances of object-based SVM, maximum likelihood (ML) and nearest neighbour (NN) classifiers using varying training set sizes. The effect of feature dimensionality on classifier accuracy was investigated in the second experiment. A SPOT 5 subscene and a four-class classification scheme were used. For the first experiment, training set sizes ranging from 4-20 per land cover class were tested. The performance of all the classifiers improved significantly as the training set size was increased. The ML classifier performed poorly when few (<10 per class) training samples were used and the NN classifier performed poorly compared to SVM throughout the experiment. SVM was the superior classifier for all training set sizes although ML achieved competitive results for sets of 12 or more training samples per class. Training sets were kept constant (20 and 10 samples per class) for the second experiment while an increasing number of features (1 to 22) were included. SVM consistently produced superior classification results. SVM and NN were not significantly (negatively) affected by an increase in feature dimensionality, but ML’s ability to perform under conditions of large feature dimensionalities and few training areas was limited. Further investigations using a variety of imagery types, classification schemes and additional features; finding optimal combinations of training set size and number of features; and determining the effect of specific features should prove valuable in developing more costeffective ways to process large volumes of satellite imagery. KEYWORDS Supervised classification, land cover, support vector machine, nearest neighbour classification maximum likelihood classification, geographic object-based image analysis
AFRIKAANSE OPSOMMING: Gerigte klassifiseerders word gereeld aangewend in afstandswaarneming om inligting oor landdekking te onttrek. Sulke klassifiseerders het egter beperkte vermoëns om akkurate landdekkingskaarte koste-effektief te produseer. Verskeie faktore het ʼn uitwerking op die akkuraatheid van gerigte klassifiseerders. Dit is veral bekend dat die getal beskikbare opleidingseenhede ʼn beduidende invloed op klassifiseerderakkuraatheid het en dit is nie altyd prakties om voldoende getalle te bekom nie. Die steunvektormasjien (SVM) werk goed met beperkte getalle opleidingseenhede. Min navorsing is egter gedoen om SVM se verrigting vir geografiese objek-gebaseerde beeldanalise (GEOBIA) te evalueer. GEOBIA vergemaklik die integrasie van addisionele kenmerke in die klassifikasie proses, ʼn faktor wat klassifikasie akkuraathede aansienlik kan beïnvloed. Twee eksperimente is gevolglik ontwikkel en geïmplementeer in hierdie navorsing. Die eerste eksperiment het objekgebaseerde SVM, maksimum waarskynlikheids- (ML) en naaste naburige (NN) klassifiseerders se verrigtings met verskillende groottes van opleidingstelle vergelyk. Die effek van kenmerkdimensionaliteit is in die tweede eksperiment ondersoek. ʼn SPOT 5 subbeeld en ʼn vier-klas klassifikasieskema is aangewend. Opleidingstelgroottes van 4-20 per landdekkingsklas is in die eerste eksperiment getoets. Die verrigting van die klassifiseerders het beduidend met ʼn toename in die grootte van die opleidingstelle verbeter. ML het swak presteer wanneer min (<10 per klas) opleidingseenhede gebruik is en NN het, in vergelyking met SVM, deurgaans swak presteer. SVM het die beste presteer vir alle groottes van opleidingstelle alhoewel ML kompeterend was vir stelle van 12 of meer opleidingseenhede per klas. Die grootte van die opleidingstelle is konstant gehou (20 en 10 eenhede per klas) in die tweede eksperiment waarin ʼn toenemende getal kenmerke (1 tot 22) toegevoeg is. SVM het deurgaans beter klassifikasieresultate gelewer. SVM en NN was nie beduidend (negatief) beïnvloed deur ʼn toename in kenmerkdimensionaliteit nie, maar ML se vermoë om te presteer onder toestande van groot kenmerkdimensionaliteite en min opleidingsareas was beperk. Verdere ondersoeke met ʼn verskeidenheid beelde, klassifikasie skemas en addisionele kenmerke; die vind van optimale kombinasies van opleidingstelgrootte en getal kenmerke; en die bepaling van die effek van spesifieke kenmerke sal waardevol wees in die ontwikkelling van meer koste effektiewe metodes om groot volumes satellietbeelde te prosesseer. TREFWOORDE Gerigte klassifikasie, landdekking, steunvektormasjien, naaste naburige klassifikasie, maksimum waarskynlikheidsklassifikasie, geografiese objekgebaseerde beeldanalise
Gavino, Christopher C. « Cost effectiveness analysis of the "Sea to SWOS" training initiative on the Surface Warfare Officer qualification process ». Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2002. http://library.nps.navy.mil/uhtbin/hyperion-image/02Dec%5FGavino.pdf.
Texte intégralThesis advisor(s): William R. Gates, William D. Hatch II. Includes bibliographical references (p. 69-73). Also available online.
Orban, Sarah. « Do programs designed to train working memory, other executive functions, and attention benefit children with ADHD ? A meta-analytic review of cognitive, academic, and behavioral outcomes ». Master's thesis, University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5997.
Texte intégralM.S.
Masters
Psychology
Sciences
Psychology Clinical
Madrigali, Andrea. « Analysis of Local Search Methods for 3D Data ». Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2016.
Trouver le texte intégralMakiou, Abdelhamid. « Sécurité des applications Web : Analyse, modélisation et détection des attaques par apprentissage automatique ». Thesis, Paris, ENST, 2016. http://www.theses.fr/2016ENST0084/document.
Texte intégralWeb applications are the backbone of modern information systems. The Internet exposure of these applications continually generates new forms of threats that can jeopardize the security of the entire information system. To counter these threats, there are robust and feature-rich solutions. These solutions are based on well-proven attack detection models, with advantages and limitations for each model. Our work consists in integrating functionalities of several models into a single solution in order to increase the detection capacity. To achieve this objective, we define in a first contribution, a classification of the threats adapted to the context of the Web applications. This classification also serves to solve some problems of scheduling analysis operations during the detection phase of the attacks. In a second contribution, we propose an architecture of Web application firewall based on two analysis models. The first is a behavioral analysis module, and the second uses the signature inspection approach. The main challenge to be addressed with this architecture is to adapt the behavioral analysis model to the context of Web applications. We are responding to this challenge by using a modeling approach of malicious behavior. Thus, it is possible to construct for each attack class its own model of abnormal behavior. To construct these models, we use classifiers based on supervised machine learning. These classifiers use learning datasets to learn the deviant behaviors of each class of attacks. Thus, a second lock in terms of the availability of the learning data has been lifted. Indeed, in a final contribution, we defined and designed a platform for automatic generation of training datasets. The data generated by this platform is standardized and categorized for each class of attacks. The learning data generation model we have developed is able to learn "from its own errors" continuously in order to produce higher quality machine learning datasets
Denecker, Thomas. « Bioinformatique et analyse de données multiomiques : principes et applications chez les levures pathogènes Candida glabrata et Candida albicans Functional networks of co-expressed genes to explore iron homeostasis processes in the pathogenic yeast Candida glabrata Efficient, quick and easy-to-use DNA replication timing analysis with START-R suite FAIR_Bioinfo : a turnkey training course and protocol for reproducible computational biology Label-free quantitative proteomics in Candida yeast species : technical and biological replicates to assess data reproducibility Rendre ses projets R plus accessibles grâce à Shiny Pixel : a content management platform for quantitative omics data Empowering the detection of ChIP-seq "basic peaks" (bPeaks) in small eukaryotic genomes with a web user-interactive interface A hypothesis-driven approach identifies CDK4 and CDK6 inhibitors as candidate drugs for treatments of adrenocortical carcinomas Characterization of the replication timing program of 6 human model cell lines ». Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASL010.
Texte intégralBiological research is changing. First, studies are often based on quantitative experimental approaches. The analysis and the interpretation of the obtained results thus need computer science and statistics. Also, together with studies focused on isolated biological objects, high throughput experimental technologies allow to capture the functioning of biological systems (identification of components as well as the interactions between them). Very large amounts of data are also available in public databases, freely reusable to solve new open questions. Finally, the data in biological research are heterogeneous (digital data, texts, images, biological sequences, etc.) and stored on multiple supports (paper or digital). Thus, "data analysis" has gradually emerged as a key research issue, and in only ten years, the field of "Bioinformatics" has been significantly changed. Having a large amount of data to answer a biological question is often not the main challenge. The real challenge is the ability of researchers to convert the data into information and then into knowledge. In this context, several biological research projects were addressed in this thesis. The first concerns the study of iron homeostasis in the pathogenic yeast Candida glabrata. The second concerns the systematic investigation of post-translational modifications of proteins in the pathogenic yeast Candida albicans. In these two projects, omics data were used: transcriptomics and proteomics. Appropriate bioinformatics and analysis tools were developed, leading to the emergence of new research hypotheses. Particular and constant attention has also been paid to the question of data reproducibility and sharing of results with the scientific community
Bonnevie, Tristan. « Nouveaux outils et optimisation des outils existants pour la réhabilitation respiratoire et la ré-autonomisation des patients atteints d'un handicap ventilatoire. Chronic obstructive pulmonary disease Six-minute stepper test to set pulmonary rehabilitation intensity in patients with COPD - a retrospective study Can the six-minute stepper test be used to determine the intensity of endurance training in early stage COPD : a multicenter observational study The six-minute stepper test is related to muscle strength but cannot substitute for the one repetition maximum to prescribe strength training in patients with COPD People undertaking pulmonary rehabilitation are willing and able to provide accurate data via a remote pulse oximetry system : a multicentre observational study Mid-term effects of pulmonary rehabilitation on cognitive function in people with severe chronic obstructive pulmonary disease NIV is not adequate for high intensity endurance in COPD Home-based neuromuscular electrical stimulation as an add-on to pulmonary rehabilitation does not provide further benefits in patients with chronic obstructive pulmonary disease : a multicenter randomized trial Lumbar transcutaneous electrical nerve stimulation to improve exercise performance in COPD patients Advanced telehealth technology improves in-home pulmonary rehabilitation for people with stable chronic obstructive pulmonary disease : a systematic review Nasal high flow for stable patients with chronic obstructive pulmonary disease : a systematic review and meta-analysis ». Thesis, Normandie, 2020. http://www.theses.fr/2020NORMR024.
Texte intégralPulmonary rehabilitation (PR) is recommended in the management of subjects with ventilatory impairment to improve their quality of life. Although a large body of evidence support its use, only few subjects benefit from it and the optimal training modality has not been determined yet. In this context, the use of new and existing tools to optimize access as well as the effects of the program are major developments that deserve to be studied. As part of this thesis, we sought to explore these two major issues (1) by considering a rehabilitation model relocated outside the PR centres while assessing the obstacles to this model and (2) exploring the effectiveness of different add-on to PR in further optimizing the benefits of the program. In the first part, we have shown, through several retrospective studies and an original prospective multicentre contribution, that the six-minute stepper test can be used to prescribe endurance training, particularly for those patients with a mild to moderate chronic obstructive pulmonary disease (COPD), but not to prescribe muscle strengthening. Furthermore, we have shown in a cohort of 105 subjects referred for PR that the use of a remote tele monitoring device was feasible, valid and widely accepted. Finally, we explored the prevalence of cognitive dysfunction, another systemic impairment of COPD that could compromise the relocation of the program, and showed that it was a very common condition (around 75% of the subjects) but that it could improve following PR and did not seem to influence the use of a remote tele monitoring device. In the second part, we evaluated the effects of different add-on used to potentiate the benefits of the PR program. In a cross-over study of 21 COPD patients, we showed that non-invasive ventilation did not improve endurance exercise capacity due to technological limitation of the ventilator. Through a multicentre randomized controlled study carried out in 73 patients with severe to very severe COPD, we have shown that neuromuscular electrical stimulation at home, performed in addition to a PR program, did not provide further benefits on quality of life or exercise capacity. Finally, through a randomized cross-over double-blind study carried out in 10 patients, we were unable to show the effectiveness of transcutaneous nerve electrical stimulation in improving their endurance exercise capacity. Finally, in a last part, we highlighted the research currently carried out in our laboratory following the original contributions described during this thesis, as well as new area of research in order to pursue the themes explored. Thus, two systematic reviews and meta-analysis (the first about nasal high flow therapy in subjects with stable COPD and the second about the use of advanced telehealth technologies to deliver PR) will serve as a basis for future research
Livres sur le sujet "Training set analysi"
Parker, A. Rani. Another point of view : A manual on gender analysis training for grassroots workers : training manual. New York : UNIFEM, 1993.
Trouver le texte intégralParker, A. Rani. Another point of view : A gender analysis training manual for grassroots workers. New York, N. Y : UNIFEM, 1993.
Trouver le texte intégralFuchsloch, Christine. Das Verbot der mittelbaren Geschlechtsdiskriminierung : Ableitung, Analyse und exemplarische Anwendung auf staatliche Berufsausbildungsförderung. Baden-Baden : Nomos, 1995.
Trouver le texte intégralBoltanova, Elena, Nataliya Bagrova, Roman Bevzenko, Svetlana Butenko, Eduard Gavrilov, Oles' Gruzdev, Valentina Kvanina et al. Civil right. Common part. ru : INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1079846.
Texte intégralWeber, Susanne. Frauenförderung : Akteure, Diagnosen und Therapievorschläge : Analyse und Kritik am Beispiel betrieblicher Weiterbildung. Bielefeld : Kleine Verlag, 1991.
Trouver le texte intégralZhukova, Galina, et Margarita Rushaylo. Mathematical analysis in examples and tasks. Part 1. ru : INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1072156.
Texte intégralPustovaya, Larisa, et Besik Meshi. Methods and devices of environmental control. Environmental monitoring. ru : INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1058966.
Texte intégralAfrican Women Development and Communication Network, dir. FEMNET training manual on gender based violence : Building skills, tools and concepts, and using them for reflection, analysis, planning, and application against gender based violence. Nairobi, Kenya : African Women's Development and Communication Network, 2003.
Trouver le texte intégralTraining of Trainers in Gender Analysis Workshop (1991 Lake Bogoria Hotel, Kenya). Report of the Training of Trainers in Gender Analysis Workshop : Held at Lake Bogoria Hotel, 18th-27th of June 1991. [Nairobi] : African Women Development and Communication Network (FEMNET), 1991.
Trouver le texte intégralLeonova, Anna, Larisa Baykova, Galina Vyalikova et Svetlana Ermolaeva. Development of the concept of teacher personality formation in the history and theory of higher pedagogical education in the 90s of the twentieth century. ru : INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1876370.
Texte intégralChapitres de livres sur le sujet "Training set analysi"
Chakraborty, Debrup. « Neural Network Ensembles from Training Set Expansions ». Dans Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 629–36. Berlin, Heidelberg : Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10268-4_74.
Texte intégralCantador, Iván, et José R. Dorronsoro. « Parallel Perceptrons, Activation Margins and Imbalanced Training Set Pruning ». Dans Pattern Recognition and Image Analysis, 43–50. Berlin, Heidelberg : Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11492542_6.
Texte intégralCastrillón-Santana, Modesto, Daniel Hernández-Sosa et Javier Lorenzo-Navarro. « Viola-Jones Based Detectors : How Much Affects the Training Set ? » Dans Pattern Recognition and Image Analysis, 297–304. Berlin, Heidelberg : Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21257-4_37.
Texte intégralFranc, Vojtěch, et Václav Hlaváč. « Greedy Algorithm for a Training Set Reduction in the Kernel Methods ». Dans Computer Analysis of Images and Patterns, 426–33. Berlin, Heidelberg : Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45179-2_53.
Texte intégralStaufer, Petra, et Manfred M. Fischer. « Spectral Pattern Recognition by a Two-Layer Perceptron : Effects of Training Set Size ». Dans Neurocomputation in Remote Sensing Data Analysis, 105–16. Berlin, Heidelberg : Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-59041-2_12.
Texte intégralAbdulhak, Sami Abduljalil, Walter Riviera, Nicola Zeni, Matteo Cristani, Roberta Ferrario et Marco Cristani. « Semantic-Analysis Object Recognition : Automatic Training Set Generation Using Textual Tags ». Dans Computer Vision - ECCV 2014 Workshops, 309–22. Cham : Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16181-5_22.
Texte intégralMartin-Gutierrez, S., J. C. Losada et R. M. Benito. « Semi-Automatic Training Set Construction for Supervised Sentiment Analysis in Polarized Contexts ». Dans Lecture Notes in Social Networks, 177–97. Cham : Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33698-1_10.
Texte intégralMcKenney, Susan. « CASCADE — SEA : Computer Assisted Curriculum Analysis, Design & ; Evaluation for Science Education in Africa ». Dans Design Approaches and Tools in Education and Training, 225–33. Dordrecht : Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4255-7_19.
Texte intégralWeiss, Mary Jane, Ksenia Gatzunis et Wafa Aljohani. « How to Integrate Multiculturalism and Diversity Sensitivity Into the Training and Ethical Skill Set of Behavior Analysts ». Dans Multiculturalism and Diversity in Applied Behavior Analysis, 167–79. New York, NY : Routledge, 2020. : Routledge, 2020. http://dx.doi.org/10.4324/9780429263873-14.
Texte intégralZhou, Yu, et Yali Wu. « Analyses on Influence of Training Data Set to Neural Network Supervised Learning Performance ». Dans Advances in Computer Science, Intelligent System and Environment, 19–25. Berlin, Heidelberg : Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23753-9_4.
Texte intégralActes de conférences sur le sujet "Training set analysi"
Ahmad, Irfan, et Gernot A. Fink. « Training an Arabic handwriting recognizer without a handwritten training data set ». Dans 2015 13th International Conference on Document Analysis and Recognition (ICDAR). IEEE, 2015. http://dx.doi.org/10.1109/icdar.2015.7333807.
Texte intégralJohnson, Timothy H., Yigah Lhamo, Lingyan Shi, Robert R. Alfano et Stewart Russell. « Fourier spatial frequency analysis for image classification : training the training set ». Dans SPIE BiOS, sous la direction de Daniel L. Farkas, Dan V. Nicolau et Robert C. Leif. SPIE, 2016. http://dx.doi.org/10.1117/12.2212934.
Texte intégralShi-Gui Li, Xiao-Ping Li, Qian Li, Chong-Guo Chen et Qi-Fan Yang. « The exploration of professional training mode based on Set Theory ». Dans 2010 International Conference on Apperceiving Computing and Intelligence Analysis (ICACIA). IEEE, 2010. http://dx.doi.org/10.1109/icacia.2010.5709949.
Texte intégralSilva, Gabriel de Franca Pereira e., Rafael Dueire Lins et Cesar Gomes. « Automatic Training Set Generation for Better Historic Document Transcription and Compression ». Dans 2014 11th IAPR International Workshop on Document Analysis Systems (DAS). IEEE, 2014. http://dx.doi.org/10.1109/das.2014.30.
Texte intégralTingting Wang et Ning Xu. « Malware variants detection based on opcode image recognition in small training set ». Dans 2017 IEEE 2nd International Conference on Cloud Computing and Big Data Analysis (ICCCBDA). IEEE, 2017. http://dx.doi.org/10.1109/icccbda.2017.7951933.
Texte intégralMartin-Gutierrez, S., J. C. Losada et R. M. Benito. « Semi-Automatic Training Set Construction for Supervised Sentiment Analysis in Political Contexts ». Dans 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE, 2018. http://dx.doi.org/10.1109/asonam.2018.8508386.
Texte intégralLiang, Guangtai, Ling Wu, Qian Wu, Qianxiang Wang, Tao Xie et Hong Mei. « Automatic construction of an effective training set for prioritizing static analysis warnings ». Dans the IEEE/ACM international conference. New York, New York, USA : ACM Press, 2010. http://dx.doi.org/10.1145/1858996.1859013.
Texte intégralTarasov, Dmitry A., et Oleg B. Milder. « The forward problem of spectral reflection prediction : Mutual match between framework selection and the training set volume ». Dans INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2019. AIP Publishing, 2020. http://dx.doi.org/10.1063/5.0026740.
Texte intégral« AUTOMATIC SELECTION OF THE TRAINING SET FOR SEMI-SUPERVISED LAND CLASSIFICATION AND SEGMENTATION OF SATELLITE IMAGES ». Dans Special Session on Pattern Recognition Applications in Remotely Sensed Hyperspectral Image Analysis. SciTePress - Science and and Technology Publications, 2012. http://dx.doi.org/10.5220/0003855504120418.
Texte intégralBahlawan, Hilal, Mirko Morini, Michele Pinelli, Pier Ruggero Spina et Mauro Venturini. « Development of Reliable NARX Models of Gas Turbine Cold, Warm and Hot Start-Up ». Dans ASME Turbo Expo 2017 : Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/gt2017-63332.
Texte intégralRapports d'organisations sur le sujet "Training set analysi"
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Texte intégralStriuk, Andrii M. Software engineering : first 50 years of formation and development. [б. в.], décembre 2018. http://dx.doi.org/10.31812/123456789/2880.
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