Adatbányászati technikák alkalmazása magyar vállalkozások adatait tartalmazó adatbázison Microsoft Excel 2007-ben

Abstract

Using a simple data mining technique, the Analyze Key Influencers, in Excel 2007 Data Mining Add-ins, we searched for relationship among the seat (county and town), the form of business, the main activity, the number of employees and the annual income of the Hungarian companies. This technique uses the Naive Bayes algorithm. According to the used method the seat has no influencers. Most of the main activities have no influencers, but some activities (82 out of 495) have relationship with the other criteria, mainly with the form of business. The form of business (all 30 categories), the number of employees (17 of 18 categories) and the annual income (all 9 categories) are each others key influencers. Cramer's association was used to check the results of the data mining. The Cramer contin-gency coefficient showed similar results as the data mining, but the results also indicated that the strength of the association was less than moderate in all cases. The highest associa-tion were between the annual income and the number of employees (0.46, moderate asso-ciation), the main activity and form of business (0.36, moderate association) and the annual income and the form of business (0.27, low association).