Dalgıçların veri madenciliği teknikleri kullanılarak sınıflandırılması
2018
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Advisor: Doç. Dr. Salih Murat Egi
Abstract (EN)
Divers Alert Network (DAN) created a database (DB) with a big amount of dive related data which has been collected since 1994 within the scope of Dive Safety Laboratory project. The aim of this study is to analyse DB using data mining techniques. The clustering of divers by their health and demographic information and revealing significant differences between diver groups are the main objectives of this study. To eliminate time effect of age, divers who participated to only one dive and one dive event were included in the study. The number of one-dive and one-event divers are 874 and 1669 respectively. Before applying clustering methods, data cleaning was performed to eliminate the potential mistakes resulting from inconsistencies, inaccuracies and missing information. TwoStep and K-means clustering methods were performed on DB to find the naturally associated clusters. Conventional statistical analysis was performed to understand differences in clusters and between male and female divers. As the result, divers were separated into 3 groups and distinguishing variables of these clusters were revealed. One dive and one event results were similar for all clusters. In order to analyse the dive-related variables with nonrecurring data, we focused on one-dive divers. The reason of this is to avoid inconsistencies in the data which changes in time. As TwoStep is suitable for categorical variables, age and dive activity years were distributed in 3 categories. For K-Means Clustering, original numerical values of these variables was used for clustering. The most distinct clusters were formed by TwoStep Clustering. The middle aged male divers without any health problem are in Cluster 1. Male and female divers with health problems and high rate of cigarette smoking are in the Cluster 2 and old divers with many dive activity years are in the Cluster 3. The search for significant differences in dive-related variables was performed based on the TwoStep Clustering results and separating male and female divers.
Author
Dr. Ahmet Cüneyt Yavuz
How to Cite
Ahmet Cüneyt Yavuz (Master Thesis). Dalgıçların veri madenciliği teknikleri kullanılarak sınıflandırılması, 2018, Galatasaray University.
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