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  • This contribution contains problems of marketing research data classification by means of data mining algorithms. Three basic methods are described, classification with the aid of Multi-layer Perceptron neural network with Back-propagation algorithm, classification with the aid of Bayesian Networks and classification with the aid of Decision Tree. Finally, applicability of these algorithms is compared. These algorithms are applied over the data from a survey about consumer behavior in the food market in the Czech Republic (n = 1127, data collection in 2011). The data were further analyzed with statistical tools, such as cluster analysis and analysis of contingency. The best achieved result was 42.65% by method LMT. Although this level may seem to be relatively low, due to the fact that also the dependencies between individual 20 factors and the 5 possible store loyalty options revealed by analysis of contingency were not strong, this result shows that the tools can reach relatively high level of accuracy even under such unfavorable conditions.
  • This contribution contains problems of marketing research data classification by means of data mining algorithms. Three basic methods are described, classification with the aid of Multi-layer Perceptron neural network with Back-propagation algorithm, classification with the aid of Bayesian Networks and classification with the aid of Decision Tree. Finally, applicability of these algorithms is compared. These algorithms are applied over the data from a survey about consumer behavior in the food market in the Czech Republic (n = 1127, data collection in 2011). The data were further analyzed with statistical tools, such as cluster analysis and analysis of contingency. The best achieved result was 42.65% by method LMT. Although this level may seem to be relatively low, due to the fact that also the dependencies between individual 20 factors and the 5 possible store loyalty options revealed by analysis of contingency were not strong, this result shows that the tools can reach relatively high level of accuracy even under such unfavorable conditions. (en)
Title
  • Exploring How Customers Shop for Meat Products
  • Exploring How Customers Shop for Meat Products (en)
skos:prefLabel
  • Exploring How Customers Shop for Meat Products
  • Exploring How Customers Shop for Meat Products (en)
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  • RIV/62156489:43110/14:00213758!RIV15-MSM-43110___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 16100
http://linked.open...ai/riv/idVysledku
  • RIV/62156489:43110/14:00213758
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Data mining; Statistical methods; Marketing Research; Loyalty; Consumer behavior; Classification (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [DB674B1FE556]
http://linked.open...v/mistoKonaniAkce
  • Cambridge, MA, USA
http://linked.open...i/riv/mistoVydani
  • Cambridge, MA, USA
http://linked.open...i/riv/nazevZdroje
  • Recent Advances in Economics, Management and Marketing
http://linked.open...in/vavai/riv/obor
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http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Motyčka, Arnošt
  • Stávková, Jana
  • Turčínek, Pavel
  • Turčínková, Jana
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
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  • WSEAS Press
https://schema.org/isbn
  • 978-960-474-364-3
http://localhost/t...ganizacniJednotka
  • 43110
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