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Comparison of the performance of multi-layer perceptron and linear regression for epidemiological data

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  • Gaudart, Jean
  • Giusiano, Bernard
  • Huiart, Laetitia

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  • Gaudart, Jean & Giusiano, Bernard & Huiart, Laetitia, 2004. "Comparison of the performance of multi-layer perceptron and linear regression for epidemiological data," Computational Statistics & Data Analysis, Elsevier, vol. 44(4), pages 547-570, January.
    • Handle: RePEc:eee:csdana:v:44:y:2004:i:4:p:547-570
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    References listed on IDEAS

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    1. Xiang, Anny & Lapuerta, Pablo & Ryutov, Alex & Buckley, Jonathan & Azen, Stanley, 2000. "Comparison of the performance of neural network methods and Cox regression for censored survival data," Computational Statistics & Data Analysis, Elsevier, vol. 34(2), pages 243-257, August.
    2. Lisi, Francesco & Schiavo, Rosa A., 1999. "A comparison between neural networks and chaotic models for exchange rate prediction," Computational Statistics & Data Analysis, Elsevier, vol. 30(1), pages 87-102, March.
    3. Capobianco, Enrico, 2000. "Neural networks and statistical inference: seeking robust and efficient learning," Computational Statistics & Data Analysis, Elsevier, vol. 32(3-4), pages 443-454, January.
    4. Tian, Jilei & Juhola, Martti & Gronfors, Tapio, 1997. "AR parameter estimation by a feedback neural network," Computational Statistics & Data Analysis, Elsevier, vol. 25(1), pages 17-24, July.
    5. Nicole, Sandro, 2000. "Feedforward neural networks for principal components extraction," Computational Statistics & Data Analysis, Elsevier, vol. 33(4), pages 425-437, June.
    6. Schumacher, Martin & Ro[ss]ner, Reinhard & Vach, Werner, 1996. "Neural networks and logistic regression: Part I," Computational Statistics & Data Analysis, Elsevier, vol. 21(6), pages 661-682, June.
    7. Vach, Werner & Ro[ss]ner, Reinhard & Schumacher, Martin, 1996. "Neural networks and logistic regression: Part II," Computational Statistics & Data Analysis, Elsevier, vol. 21(6), pages 683-701, June.
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    1. Yanfeng Wang & Haohao Wang & Sanyi Li & Lidong Wang, 2022. "Survival Risk Prediction of Esophageal Cancer Based on the Kohonen Network Clustering Algorithm and Kernel Extreme Learning Machine," Mathematics, MDPI, vol. 10(9), pages 1-20, April.
    2. Piasecki Krzysztof & Wójcicka-Wójtowicz Aleksandra, 2017. "Capacity of Neural Networks and Discriminant Analysis in Classifying Potential Debtors," Folia Oeconomica Stetinensia, Sciendo, vol. 17(2), pages 129-143, December.
    3. Indy Man Kit Ho & Kai Yuen Cheong & Anthony Weldon, 2021. "Predicting student satisfaction of emergency remote learning in higher education during COVID-19 using machine learning techniques," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-27, April.
    4. van der Kooij, Anita J. & Meulman, Jacqueline J. & Heiser, Willem J., 2006. "Local minima in categorical multiple regression," Computational Statistics & Data Analysis, Elsevier, vol. 50(2), pages 446-462, January.
    5. Shiyi Chen & Kiho Jeong & Wolfgang K. Härdle, 2008. "Recurrent Support Vector Regression for a Nonlinear ARMA Model with Applications to Forecasting Financial Returns," SFB 649 Discussion Papers SFB649DP2008-051, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    6. Walde, Janette F., 2007. "Valid hypothesis testing in face of spatially dependent data using multi-layer perceptrons and sub-sampling techniques," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2701-2719, February.
    7. Shiyi Chen & Kiho Jeong & Wolfgang Härdle, 2015. "Recurrent support vector regression for a non-linear ARMA model with applications to forecasting financial returns," Computational Statistics, Springer, vol. 30(3), pages 821-843, September.

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