Mostrar el registro sencillo del ítem

dc.contributor.authorFontalvo Herrera, Tomas
dc.contributor.authorDe La Hoz Dominguez, Enrique
dc.date.accessioned2023-07-14T13:47:54Z
dc.date.available2023-07-14T13:47:54Z
dc.date.issued2019-04
dc.date.submitted2023-07
dc.identifier.urihttps://hdl.handle.net/20.500.12585/12096
dc.description.abstractn this research, a classification model is developed for the banking sector using the machine earning technique GLMNET. In the first place, a clustering process was developed, where 3 clearly differentiated groups were found. Subsequently, a Fuzzy analysis was performed finding the probabilities of transition of the banks to each group found, finally, the GLMNET algorithm was implemented, the automatic classification of the banks according to their financial items, obtaining a result of 95% accuracy. © 2019 International Business Information Management Association (IBIMA).spa
dc.format.extent10 páginas
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceProceedings of the 33rd International Business Information Management Association Conference, IBIMA 2019: Education Excellence and Innovation Management through Vision 2020spa
dc.titleA machine learning approach for banks classification and forecastspa
dcterms.bibliographicCitationAcuna, E., Rodriguez, C. The treatment of missing values and its effect on classifier accuracy (2004) Classification, Clustering, and Data Mining Applications, pp. 639-647. Cited 404 times. Springer, Berlin, Heidelbergspa
dcterms.bibliographicCitationAmores-Salvadó, J., Martin-de Castro, G., Navas-López, J.E. The importance of the complementarity between environmental management systems and environmental innovation capabilities: A firm level approach to environmental and business performance benefits (2015) Technological Forecasting and Social Change, 96, pp. 288-297. Cited 84 times. www.elsevier.com/inca/publications/store/5/0/5/7/4/0/ doi: 10.1016/j.techfore.2015.04.004spa
dcterms.bibliographicCitationBüyüközkan, G., Kayakutlu, G., Karakadilar, I.S. Assessment of lean manufacturing effect on business performance using Bayesian Belief Networks (2015) Expert Systems with Applications, 42 (19), pp. 6539-6551. Cited 62 times. doi: 10.1016/j.eswa.2015.04.016spa
dcterms.bibliographicCitationCastillo, P.A., Mora, A.M., Faris, H., Merelo, J.J., García-Sánchez, P., Fernández-Ares, A.J., De las Cuevas, P., (...), García-Arenas, M.I. Applying computational intelligence methods for predicting the sales of newly published books in a real editorial business management environment (2017) Knowledge-Based Systems, 115, pp. 133-151. Cited 27 times. doi: 10.1016/j.knosys.2016.10.019spa
dcterms.bibliographicCitationCavalcante, R.C., Brasileiro, R.C., Souza, V.L.F., Nobrega, J.P., Oliveira, A.L.I. Computational Intelligence and Financial Markets: A Survey and Future Directions (2016) Expert Systems with Applications, 55, pp. 194-211. Cited 355 times. doi: 10.1016/j.eswa.2016.02.006spa
dcterms.bibliographicCitationChen, M.-S., Han, J., Yu, P.S. Data mining: An overview from a database perspective (1996) IEEE Transactions on Knowledge and Data Engineering, 8 (6), pp. 866-883. Cited 1560 times. doi: 10.1109/69.553155spa
dcterms.bibliographicCitationDietterich, T.G. Ensemble methods in machine learning (2000) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1857 LNCS, pp. 1-15. Cited 4615 times. https://www.springer.com/series/558 ISBN: 3540677046; 978-354067704-8 doi: 10.1007/3-540-45014-9_1spa
dcterms.bibliographicCitationDutta, A., Bandopadhyay, G., Sengupta, S. Prediction of stock performance in indian stock market using logistic regression (2015) International Journal of Business and Information, 7 (1). Cited 48 times.spa
dcterms.bibliographicCitationFriedman, J., Hastie, T., Tibshirani, R. Regularization paths for generalized linear models via coordinate descent (2010) Journal of Statistical Software, 33 (1), pp. 1-22. Cited 9422 times. http://www.jstatsoft.org/v33/i01/paper doi: 10.18637/jss.v033.i01spa
dcterms.bibliographicCitationHans, C. Bayesian lasso regression (Open Access) (2009) Biometrika, 96 (4), pp. 835-845. Cited 274 times. doi: 10.1093/biomet/asp047spa
dcterms.bibliographicCitationHoerl, A.E., Kennard, R.W. Ridge Regression: Biased Estimation for Nonorthogonal Problems (1970) Technometrics, 12 (1), pp. 55-67. Cited 6972 times. doi: 10.1080/00401706.1970.10488634spa
dcterms.bibliographicCitationInce, H., Trafalis, T.B. Short term forecasting with support vector machines and application to stock price prediction (2008) International Journal of General Systems, 37 (6), pp. 677-687. Cited 64 times. www.tandf.co.uk/journals/titles/03081079.asp doi: 10.1080/03081070601068595spa
dcterms.bibliographicCitationKarnizova, L., Li, J.C. Economic policy uncertainty, financial markets and probability of US recessions (2014) Economics Letters, 125 (2), pp. 261-265. Cited 153 times. http://www.elsevier.com/homepage/sae/econbase/ecolet/ doi: 10.1016/j.econlet.2014.09.018spa
dcterms.bibliographicCitationKaufman, L., Rousseeuw, P.J. Partitioning around medoids (program pam) (1990) Finding Groups in Data: An Introduction to Cluster Analysis, pp. 68-125. Cited 430 times.spa
dcterms.bibliographicCitationKauko, K., Palmroos, P. The Delphi method in forecasting financial markets-An experimental study (2014) International Journal of Forecasting, 30 (2), pp. 313-327. Cited 62 times. doi: 10.1016/j.ijforecast.2013.09.007spa
dcterms.bibliographicCitationKim, G., Bae, J. A novel approach to forecast promising technology through patent analysis (2017) Technological Forecasting and Social Change, 117, pp. 228-237. Cited 115 times. www.elsevier.com/inca/publications/store/5/0/5/7/4/0/ doi: 10.1016/j.techfore.2016.11.023spa
dcterms.bibliographicCitationLam, S.K., Sleep, S., Hennig-Thurau, T., Sridhar, S., Saboo, A.R. Leveraging Frontline Employees’ Small Data and Firm-Level Big Data in Frontline Management: An Absorptive Capacity Perspective (2017) Journal of Service Research, 20 (1), pp. 12-28. Cited 60 times. http://www.sagepub.co.uk/journal.aspx?pid=105683 doi: 10.1177/1094670516679271spa
dcterms.bibliographicCitationLi, X., Pan, B., Law, R., Huang, X. Forecasting tourism demand with composite search index (Open Access) (2017) Tourism Management, 59, pp. 57-66. Cited 233 times. www.elsevier.com/inca/publications/store/3/0/4/7/2/ doi: 10.1016/j.tourman.2016.07.005spa
dcterms.bibliographicCitationMacQueen, J. (1967) Some Methods for Classification and Analysis of Multivariate Observations, 1, pp. 281-297. Cited 19800 times. Oakland, CA, USAspa
dcterms.bibliographicCitationMcCullagh, P. Generalized linear models (Open Access) (1984) European Journal of Operational Research, 16 (3), pp. 285-292. Cited 296 times. doi: 10.1016/0377-2217(84)90282-0spa
dcterms.bibliographicCitationMicallef, L., Sundin, I., Marttinen, P., Ammad-Ud-din, M., Peltola, T., Soare, M., Jacucci, G., (...), Kaski, S. Interactive elicitation of knowledge on feature relevance improves predictions in small data sets (2017) International Conference on Intelligent User Interfaces, Proceedings IUI, pp. 547-552. Cited 18 times. ISBN: 978-145034348-0 doi: 10.1145/3025171.3025181spa
dcterms.bibliographicCitationPuri, J., Yadav, S.P. Intuitionistic fuzzy data envelopment analysis: An application to the banking sector in India (2015) Expert Systems with Applications, 42 (11), pp. 4982-4998. Cited 55 times. doi: 10.1016/j.eswa.2015.02.014spa
dcterms.bibliographicCitationRamirez, A., Lopez, I., Villuendas, Y., Yanez, C. Evolutive improvement of parameters in an associative classifier (2015) IEEE Latin America Transactions, 13 (5), art. no. 7112014, pp. 1550-1555. Cited 14 times. http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=9907 doi: 10.1109/TLA.2015.7112014spa
dcterms.bibliographicCitationSteyerberg, E.W., Eijkemans, M.J.C., Harrell Jr., F.E., Habbema, J.D.F. Prognostic modeling with logistic regression analysis: In search of a sensible strategy in small data sets (Open Access) (2001) Medical Decision Making, 21 (1), pp. 45-56. Cited 421 times. http://mdm.sagepub.com/content/by/year doi: 10.1177/0272989X0102100106spa
dcterms.bibliographicCitationSchneider, M.J., Gupta, S. Forecasting sales of new and existing products using consumer reviews: A random projections approach (2016) International Journal of Forecasting, 32 (2), pp. 243-256. Cited 62 times. http://www.elsevier.com/locate/ijforecast doi: 10.1016/j.ijforecast.2015.08.005spa
dcterms.bibliographicCitationSuominen, A., Toivanen, H., Seppänen, M. Firms' knowledge profiles: Mapping patent data with unsupervised learning (2017) Technological Forecasting and Social Change, 115, pp. 131-142. Cited 67 times. www.elsevier.com/inca/publications/store/5/0/5/7/4/0/ doi: 10.1016/j.techfore.2016.09.028spa
dcterms.bibliographicCitationThoma, G. Composite value index of patent indicators: Factor analysis combining bibliographic and survey datasets (Open Access) (2014) World Patent Information, 38, pp. 19-26. Cited 34 times. http://www.elsevier.com/locate/issn/01722190 doi: 10.1016/j.wpi.2014.05.005spa
dcterms.bibliographicCitationTkáč, M., Verner, R. Artificial neural networks in business: Two decades of research (Open Access) (2016) Applied Soft Computing Journal, 38, pp. 788-804. Cited 226 times. http://www.elsevier.com/wps/find/journaldescription.cws_home/621920/description#description doi: 10.1016/j.asoc.2015.09.040spa
dcterms.bibliographicCitationWard, J.H. Hierarchical Grouping to Optimize an Objective Function (Open Access) (1963) Journal of the American Statistical Association, 58 (301), pp. 236-244. Cited 13727 times. doi: 10.1080/01621459.1963.10500845spa
dcterms.bibliographicCitationZou, H., Hastie, T. Regularization and variable selection via the elastic net (2005) Journal of the Royal Statistical Society. Series B: Statistical Methodology, 67 (2), pp. 301-320. Cited 10640 times. doi: 10.1111/j.1467-9868.2005.00503.xspa
datacite.rightshttp://purl.org/coar/access_right/c_abf2spa
oaire.versionhttp://purl.org/coar/version/c_b1a7d7d4d402bccespa
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.hasversioninfo:eu-repo/semantics/draftspa
dc.subject.keywordsCustomer Churn;spa
dc.subject.keywordsSales;spa
dc.subject.keywordsCustomer Relationship Managementspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.ccAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.identifier.instnameUniversidad Tecnológica de Bolívarspa
dc.identifier.reponameRepositorio Universidad Tecnológica de Bolívarspa
dc.publisher.placeCartagena de Indiasspa
dc.subject.armarcLEMB
dc.type.spahttp://purl.org/coar/resource_type/c_6501spa
oaire.resourcetypehttp://purl.org/coar/resource_type/c_6501spa


Ficheros en el ítem

Thumbnail
Thumbnail

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem

http://creativecommons.org/licenses/by-nc-nd/4.0/
http://creativecommons.org/licenses/by-nc-nd/4.0/

Universidad Tecnológica de Bolívar - 2017 Institución de Educación Superior sujeta a inspección y vigilancia por el Ministerio de Educación Nacional. Resolución No 961 del 26 de octubre de 1970 a través de la cual la Gobernación de Bolívar otorga la Personería Jurídica a la Universidad Tecnológica de Bolívar.