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- W2534425741 abstract "Data election to build a representative model able to explain socio-economic phenomena is a challenge within themodel construction stage itself. Knowing what data to includewithin the studies and what to discard is a challenge, and again, at the same time, a great amount of possible factors affectingeach variable behavior must be found. In complex phenomena, the number of factors affecting a variable is enormous, andisolating a variable can become a hopeless effort. Besides, thereare also factors that are difficultly observable or inherentlynot observable that must be considered, those ones known aserrors or perturbations in a relation that have influence inthe constructed model outputs. Techniques applied in datamining can give support to the studies in the moment ofanalyzing the socio-economic phenomena and demonstrateresults obtained through a scientific and reliable way. Datamining is proposed as a valid option in the study of indicatorscontrasting the traditional methodology (econometrics). Anexperiment was conducted to contrast two cultures in the use ofstatistical modeling. One assumes that the data are generatedby stochastic GIVEN data model (Data Modeling Culture). The other one uses algorithmic models and treats the data as unknown mechanism (Algorithmic Modeling Culture)." @default.
- W2534425741 created "2016-10-28" @default.
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- W2534425741 date "2015-09-01" @default.
- W2534425741 modified "2023-09-23" @default.
- W2534425741 title "Predictive Models of Economic Systems Based on Data Mining" @default.
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- W2534425741 doi "https://doi.org/10.1109/dmia.2015.20" @default.
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