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DEVELOPMENT OF DATA MINING MODELS FOR ANALYSIS OF CHARACTERISTICS OF UNEMPLOYED PERSONS AND PREDICTING OF UNEMPLOYMENT DURATION (Polish title below)

100%

Lasek M. , Peczkowski M.

Optimum. Studia Ekonomiczne

2012

nr 1(55)

119-142

(Polish title: Budowa modeli eksploracji danych (data mining) na potrzeby analiz cech charakteryzujacych osoby bezrobotne i przewidywania pozostania osoba bezrobotna). The article discusses data mining models that can be useful in the analysis of attributes influencing individual unemployment and can help to estimate the probability with which persons with certain characteristics (age, education, gender, family background, family status, family size etc.) are more likely to be unemployed or to lose their job. Three models were constructed, and verified, to accomplish this task: logistic regression, multilayered neural network and decision tree. The study was based on Polish official statistical data. SAS Enterprise Miner software from SAS Institute Inc. was applied for model construction and data analysis.

ANALYSIS OF IMPACT OF USING THE TREND VARIABLES ON BANKRUPTCY PREDICTION MODELS PERFORMANCE

100%

Gavurová B. , Janke F. , Packová M.

Ekonomický časopis (Journal of Economics)

2017

tom 65

nr 4

370 – 383

The main objective of this paper is to analyse the impact of trend variables on the predictive ability of the models constructed using two methods: discriminant analysis and decision tree technique. The second objective is to develop a new model with prediction accuracy higher by at least 10% in comparison with other models being currently used in the Slovak business environment (Altman model, Index IN05). After analysing and comparing these methods, we came to the conclusion that the most suitable method for developing the model was the decision tree technique. Using this technique we were able to extract classification rules for bankruptcy prediction and achieve predictive ability of about 85% which, in comparison with other models, showed higher predictive performance by about 10%. Moreover, we confirmed that by applying the dynamic approach predictive ability of the decision tree increased; however we did not derive the same result using the discriminant analysis method.

THE SUBJECTIVE MARKETING RISKS AT DEVELOPING AND ENTERING THE INNOVATIVE PRODUCTS TO THE MARKET (Urakhuvannia subiektyvnykh marketynhovykh ryzykiv pry rozroblenni ta vyvedenni innovatsiinoi produktsii na rynok)

75%

Bilovodska O. A.

Mekhanizm Rehuluvannya Economiky

2010

tom 1 (45)

96-103

In paper the subjective marketing risks are analysed, kinds and factors of these risks on each of stages developing and entering the innovative products to the market are found out, their quantitative estimation is executed and the proper methods of decline are offered.