IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/97305.html
   My bibliography  Save this paper

Searching for Interpretable Demographic Patterns

Author

Listed:
  • Muratova, Anna
  • Islam, Robiul
  • Mitrofanova, Ekaterina S.
  • Ignatov, Dmitry I.

Abstract

Nowadays there is a large amount of demographic data which should be analyzed and interpreted. From accumulated demographic data, more useful information can be extracted by applying modern methods of data mining. Two kinds of experiments are considered in this work: 1) generation of additional secondary features from events and evaluation of its influence on accuracy; 2) exploration of features influence on classification result using SHAP (SHapley Additive exPlanations). An algorithm for creating secondary features is proposed and applied to the dataset. The classifications were made by two methods, SVM and neural networks, and the results were evaluated. The impact of events and features on the classification results was evaluated using SHAP; it was demonstrated how to tune model for improving accuracy based on the obtained values. Applying convolutional neural network for sequences of events allowed improve classification accuracy and surpass the previous best result on the studied demographic dataset.

Suggested Citation

  • Muratova, Anna & Islam, Robiul & Mitrofanova, Ekaterina S. & Ignatov, Dmitry I., 2019. "Searching for Interpretable Demographic Patterns," MPRA Paper 97305, University Library of Munich, Germany, revised 23 Sep 2019.
  • Handle: RePEc:pra:mprapa:97305
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/97305/1/paper2.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    data mining; demographics; neural networks; classification; SHAP; interpretation;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • I00 - Health, Education, and Welfare - - General - - - General
    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:97305. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Joachim Winter). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.