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Original scientific paper

https://doi.org/10.19279/TVZ.PD.2020-8-1-05

APPLICATION OF DATA MINING AND MACHINE LEARNING ALGORITHMS FOR CLASSIFICATION AND PREDICTION IN THE SOCIAL AREA

Sanja Kraljević ; Zagreb University of Applied Sciences, Zagreb, Croatia
Ognjen Staničić ; Zagreb University of Applied Sciences, Zagreb, Croatia


Full text: croatian pdf 1.146 Kb

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Abstract

In this paper knowledge discovery is analyzed using machine learning methods from a database of a web application from the social field. Data mining is performed using four differend methods on a database linked to registrations and attendance of business events organized by a company in a three year span. The primary objective of the paper is to discover knowledge from an existing data set. New knowledge was discovered using descriptive deep analysis using the decision tree method, random forests, rule induction and the support vector machine. Differences between methods are studied, advantages and flaws with emphasis on precision and time consumption. The process of data preparation, which takes the most time, and numerical results yielded in the predictive analysis are also shown in this paper.

Keywords

knowledge discovery; dana mining; artificial intelligence; machine learning; classification; prediction; decision tree; random forests; rule induction; support vector machine; event

Hrčak ID:

242766

URI

https://hrcak.srce.hr/242766

Publication date:

17.6.2020.

Article data in other languages: croatian

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