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Deep Learning for Distribution Channels' Management

Listed author(s):
  • Sabina-Cristiana NECULA

    ()

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    This paper presents an experiment of using deep learning models for distribution channel management. We present an approach that combines self-organizing maps with artificial neural network with multiple hidden layers in order to identify the potential sales that might be addressed for channel distribution change/ management. Our study aims to highlight the evolution of techniques from simple features/learners to more complex learners and feature engineering or sampling techniques. This paper will allow researchers to choose best suited techniques and features to prepare their churn prediction models.

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    File URL: http://revistaie.ase.ro/content/84/06%20-%20necula.pdf
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    Article provided by Academy of Economic Studies - Bucharest, Romania in its journal Informatica Economica.

    Volume (Year): 21 (2017)
    Issue (Month): 4 ()
    Pages: 73-84

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    Handle: RePEc:aes:infoec:v:21:y:2017:i:4:p:73-84
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