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Neural networks and logistic regression: Part II

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  • Vach, Werner
  • Ro[ss]ner, Reinhard
  • Schumacher, Martin

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  • 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.
    • Handle: RePEc:eee:csdana:v:21:y:1996:i:6:p:683-701
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    Cited by:

    1. Jiangping Gao & Xiangyang Shi & Linghui Li & Ziqiang Zhou & Junfeng Wang, 2022. "Assessment of Landslide Susceptibility Using Different Machine Learning Methods in Longnan City, China," Sustainability, MDPI, vol. 14(24), pages 1-26, December.
    2. 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.
    3. H. Pourghasemi & H. Moradi & S. Fatemi Aghda, 2013. "Landslide susceptibility mapping by binary logistic regression, analytical hierarchy process, and statistical index models and assessment of their performances," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 69(1), pages 749-779, October.
    4. Alex Nosenko & Yuan Cheng & Haiquan Chen, 2023. "Password and Passphrase Guessing with Recurrent Neural Networks," Information Systems Frontiers, Springer, vol. 25(2), pages 549-565, April.
    5. Reggiani, Aura & Nijkamp, Peter & Nobilio, Lucia, 1997. "Spatial modal patterns in European freight transport networks: results of neurocomputing and logit models," Serie Research Memoranda 0029, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    6. 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.
    7. Manojit Chattopadhyay & Subrata Kumar Mitra, 2017. "Applicability and effectiveness of classifications models for achieving the twin objectives of growth and outreach of microfinance institutions," Computational and Mathematical Organization Theory, Springer, vol. 23(4), pages 451-474, December.
    8. Leo Liberti, 2020. "Distance geometry and data science," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 271-339, July.
    9. Zhang, G. Peter & Keil, Mark & Rai, Arun & Mann, Joan, 2003. "Predicting information technology project escalation: A neural network approach," European Journal of Operational Research, Elsevier, vol. 146(1), pages 115-129, April.
    10. Rabiu Muazu Musa & Anwar P. P. Abdul Majeed & Zahari Taha & Siow Wee Chang & Ahmad Fakhri Ab. Nasir & Mohamad Razali Abdullah, 2019. "A machine learning approach of predicting high potential archers by means of physical fitness indicators," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-12, January.

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