Cluster description using fuzzy logic. | [Proceedings of International Conference on Information Communication Technologies • 2008]

Author(s):

1. Nafees-Ur-Rehman: Institute of Management Sciences Peshawar khyber pakhtunkhwa, Pakistan

2. Fazal Masud Kundi: Institute of Computing & Information Technology, Gomal University, khyber pakhtunkhwa, Pakistan

3. Aurangzeb Khan: University of Science & Technology Bannu, Khyber Pakhtunkhwa, Pakistan

4. Amjadullah: University of Engineering and Technology, Peshawar, Khyber Pakhtunkhwa, Pakistan

Abstract:

The two primary goals of data mining tend to be prediction and description. Prediction involves using some variables or fields in the data set to predict unknown or future values of other variables of interest. Description, on the other hand, focuses on finding patterns describing the data that can be interpreted by humans. Their work is concerned with the description of clusters. Clustering methods group data according some common properties, but the deficiency lies in labeling a cluster. To grasp an understanding one has to look into the contents of the clusters. The authors work tries to label clusters according to their contents so that a first look understanding about the clusters can be achieved. For this, the authors have combined fuzzy logic to label clusters by qualitative terms. A mapping algorithm is also written to perform this cluster labeling. The process of mapping and the definition of fuzzy sets is user oriented. Their experimental results showed that the descriptive labels have been assigned according to the temperature clusters.

Page(s): 7-10

DOI: DOI not available

Published: Journal: Proceedings of International Conference on Information Communication Technologies, Volume: 27, Issue: 0, Year: 2008

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