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

• Authors: Lasek Miroslawa , Peczkowski Marek
• Languages of publication: PL

Abstracts

EN

(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.

Keywords

EN

DATA MINING   DECISION TREE   LOGISTIC REGRESSION MODEL   UNEMPLOYMENT  

Discipline

• ECONOMICS: ECONOMICS

• Publisher: Bialystok University Press
• Journal: Optimum. Studia Ekonomiczne
• Year: 2012
• Issue: 1(55)
• Pages: 119-142
• Document type: ARTICLE

Contributors

author

Lasek Miroslawa,

author

Peczkowski Marek

• Prof. Miroslawa Lasek, Mgr Marek Peczkowski - Wydzial Nauk Ekonomicznych Uniwersytetu Warszawskiego

Identifiers

CEJSH db identifier

11PLAAAA109424