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  • Search: subject:"support vector machine"
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Year of publication
Subject
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Mustererkennung 159 Pattern recognition 158 Prognoseverfahren 89 Forecasting model 80 Theorie 80 Theory 70 Artificial intelligence 54 Künstliche Intelligenz 54 Neuronale Netze 40 Neural networks 38 Kreditwürdigkeit 36 Support Vector Machine 36 support vector machine 29 Credit rating 28 Regression analysis 26 Regressionsanalyse 26 Algorithm 25 Algorithmus 25 Classification 24 Klassifikation 22 Support vector machine 16 Data Mining 15 Schätzung 15 machine learning 15 Forecast 14 Insolvency 14 Insolvenz 14 Prognose 14 Deutschland 13 Machine learning 13 Börsenkurs 12 Data mining 12 Estimation 11 Kreditrisiko 11 Share price 11 Support Vector Machines 11 random forest 11 support vector machines 11 Cluster analysis 10 Clusteranalyse 10
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Online availability
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Free 212 CC license 33
Type of publication
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Book / Working Paper 129 Article 83
Type of publication (narrower categories)
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Working Paper 73 Article in journal 62 Aufsatz in Zeitschrift 62 Arbeitspapier 56 Graue Literatur 54 Non-commercial literature 54 Article 15 Hochschulschrift 4 Thesis 3 Forschungsbericht 1 research-article 1
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Language
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English 194 Undetermined 9 German 6 Spanish 3
Author
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Härdle, Wolfgang 22 Härdle, Wolfgang Karl 12 Schäfer, Dorothea 12 Chen, Shiyi 10 Moro, Rouslan 8 Moro, Rouslan A. 8 Christmann, Andreas 7 Gründler, Klaus 6 Hoffmann, Linda 6 Jeong, Kiho 6 Krieger, Tommy 6 Rüping, Stefan 6 Lee, Yuh-Jye 5 León, Carlos 5 Papadimitriou, Theophilos 5 Yeh, Yi-Ren 5 Aliakbari, Saeideh 4 Huang, Shian-Chang 4 Michelsen, Claus 4 Moro, Russ 4 Auria, Laura 3 Bioch, Jan C. 3 Cely, Jorge 3 Girotra, Karan 3 Gkonkas, Periklēs 3 Groenen, Patrick J. F. 3 Hashemi, Leila 3 Jasemi, Milad 3 Mahmoodi, Armin 3 Moro, R. A. 3 Stathakis, Efthymios 3 Steinwart, Ingo 3 Ulrich, Karl T. 3 Acero, Oscar 2 Anagnostopoulos, Theodoros 2 Aparicio, Juan 2 Azimi, Mohammadamin 2 Barucca, Paolo 2 Bildirici, Melike 2 Brédart, Xavier 2
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Institution
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Institut für Wirtschafts- und Sozialstatistik, Universität Dortmund 3 Sonderforschungsbereich 649: Ökonomisches Risiko, Wirtschaftswissenschaftliche Fakultät 3 Deutsche Bundesbank 1 Deutsches Institut für Wirtschaftsforschung 1 Faculteit Economie en Bedrijfskunde, Universiteit Gent 1 Faculteit Toegepaste Economische Wetenschappen, Universiteit Antwerpen 1 Institut de Préparation à l'Administration et à la Gestion (IPAG) 1 International Institute of Social and Economic Sciences 1 Università degli Studi di Milano / Dipartimento di Economia Politica e Aziendale 1 Volkswirtschaftliche Fakultät, Ludwig-Maximilians-Universität München 1
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Published in...
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Technical report / Sonderforschungsbereich 475 Komplexitätsreduktion in Multivariaten Datenstrukturen, Universität Dortmund 9 SFB 649 Discussion Paper 8 SFB 649 discussion paper 8 Financial innovation : FIN 5 Journal of risk and financial management : JRFM 5 Risks : open access journal 5 Decision analytics journal 4 Econometric Institute research papers 4 Journal of Risk and Financial Management 4 CESifo working papers 3 DIW Discussion Papers 3 Discussion papers / Deutsches Institut für Wirtschaftsforschung 3 Energies 3 SFB 649 Discussion Papers 3 Technical Report 3 Technical Reports / Institut für Wirtschafts- und Sozialstatistik, Universität Dortmund 3 Borradores de economía 2 Computer Science Preprint Archive 2 Data science and management : DSM 2 Diskussionspapiere des Lehrstuhls / Lehrstuhl für Volkswirtschaftslehre, insbesondere Wirtschaftsordnung und Sozialpolitik 2 Economics discussion papers 2 Faculty & research / Insead : working paper series 2 Finance and economics discussion series 2 Financial Innovation 2 Global Business & Finance Review (GBFR) 2 Global business and finance review 2 International Journal of Financial Studies : open access journal 2 Iranian economic review : journal of University of Tehran 2 IÖR-Schriften 2 Technology audit and production reserves 2 Top : an official journal of the Spanish Society of Statistics and Operations Research 2 13th International Conference on Econometrics, Operations Research, and Statistics, 24-26 May 2012, Famagusta, Cyprus 1 Análisis económico 1 Asian journal of economics and banking : AJEB 1 BSP working paper series 1 Bank of Japan working paper series 1 Bundesbank Series 2 Discussion Paper 1 CBN journal of applied statistics 1 Cardiff Economics Working Papers 1 Cardiff economics working papers 1
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Source
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ECONIS (ZBW) 162 EconStor 32 RePEc 16 BASE 1 Other ZBW resources 1
Showing 1 - 10 of 212
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Intelligent policy framework : natural resource conservation, knowledge and big data analytics
Xiao, Nina; Qu, Xianhe - In: Journal of innovation & knowledge : JIK 10 (2025) 2, pp. 1-10
study employed two algorithms: Bayesian inference and a weighted Support Vector Machine (SVM) algorithm based on the grey …
Persistent link: https://www.econbiz.de/10015331637
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Identifying marriage markets
Bolletta, Ugo; Cherchye, Laurens; Demuynck, Thomas; … - 2024
Persistent link: https://www.econbiz.de/10015050255
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A performance analysis of stochastic processes and machine learning algorithms in stock market prediction
Bouasabah, Mohammed - In: Economies : open access journal 12 (2024) 8, pp. 1-12
geometric Brownian motion (GBM) models, with that of machine learning algorithms, such as Random Forest, Support Vector Machine …
Persistent link: https://www.econbiz.de/10015070753
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A novel fusion Support Vector Machine integrating weak and sphere models for classification challenges with massive data
Pimentel, Jonatha Sousa; Ospina, Raydonal; Ara, Anderson - In: Decision analytics journal 11 (2024), pp. 1-14
incorporating weak and sphere support vector machine to address classification challenges with massive datasets. Comparative … Vector Machine (SVM) is a powerful machine learning tool that has proven invaluable in classifying observations through …The unprecedented growth in data generation has necessitated the adoption of advanced analytical techniques. Support …
Persistent link: https://www.econbiz.de/10015101975
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Financial distress prediction using artificial neural network partial least squares regression support vector machine hybrid model and logit model
Osoolian, Mohammad; Varahrami, Vida; Razavi, Hoda - In: Iranian economic review : journal of University of Tehran 28 (2024) 3, pp. 1022-1049
Persistent link: https://www.econbiz.de/10015402991
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A comparative assessment of machine learning algorithms with the Least Absolute Shrinkage and Selection Operator for breast cancer detection and prediction
Hassan, Md. Mehedi; Hassan, Md. Mahedi; Yasmin, Farhana; … - In: Decision analytics journal 7 (2023), pp. 1-17
Boosting (XGB), Gradient Boosting (GB), Random Forest (RF), Multilayer Perceptron (MLP), and Support Vector Machine (SVM …
Persistent link: https://www.econbiz.de/10014497358
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Is artificial intelligence really more accurate in predicting bankruptcy?
Letkovský, Stanislav; Jeňcová, Sylvia; … - In: International Journal of Financial Studies : open … 12 (2024) 1, pp. 1-19
Predicting bankruptcy within selected industries is crucial because of the potential ripple effects and unique characteristics of those industries. It serves as a risk management tool, guiding various stakeholders in making decisions. While artificial intelligence (AI) has shown high success...
Persistent link: https://www.econbiz.de/10014502270
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Forecasting stock closing prices with an application to airline company data
Xu, Xu; Zhang, Yixiang; McGrory, Clare Anne; Wu, Jinran; … - In: Data science and management : DSM 6 (2023) 4, pp. 239-246
also compare our approach with ridge, tree, and support vector machine regressions, as well as neural network approaches to …
Persistent link: https://www.econbiz.de/10014518025
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Prediction and analysis of customer complaints using machine learning techniques
Alarifi, Ghadah; Rahman, Mst Farjana; Hossain, Md Shamim - In: International journal of e-business research : IJEBR ; … 19 (2023) 1, pp. 1-25
Persistent link: https://www.econbiz.de/10015051113
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Identification of best discrimination surface by mixed-integer semi-definite programming for support vector machine
Tanaka, Katsuhiro; Yamamoto, Rei - In: International journal of financial engineering 9 (2022) 4, pp. 1-16
Persistent link: https://www.econbiz.de/10014234343
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