Mining the World Bank Data: The Fuzzy C-means Clustering Approach

Author

Iveta Mrazova
Cihan H. Dagli, Missouri University of Science and TechnologyFollow

Abstract

The World Development Indicators (WDI) provide comparative socioeconomic data for state economies. With regard to imprecisions and incompleteness in the collected data, we use fuzzy c-means clustering algorithm (FCM) to group the economies according to their mutual similarities. To determine the appropriate number of clusters, various criteria are examined.

Recommended Citation

I. Mrazova and C. H. Dagli, "Mining the World Bank Data: The Fuzzy C-means Clustering Approach," Intelligent Engineering Systems Through Artificial Neural Networks, American Society of Mechanical Engineers (ASME), Jan 2003.

Department(s)

Engineering Management and Systems Engineering

Keywords and Phrases

Data Acquisition; Data Mining; Data Reduction; Data Sets; Economics; Fuzzy Sets

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2003 American Society of Mechanical Engineers (ASME), All rights reserved.

Publication Date

01 Jan 2003