Unsupervised Learning Method Based on Partitioning in Data Mining
2015
0 views
0 downloads
Advisor: Ersin Kuset Bodur
Abstract (EN)
This study provides the introduction of some basic definitions about clustering method of data mining. For this purpose, it is given the methods of data mining, some algorithms of clustering method. Meanwhile, the k -Means clustering and Hierarchical clustering algorithms are defined. The aim of this study is to cluster the dataset into two clusters using Hierarchical clustering algorithm and k -Means algorithm. In order to achieve our target, two distance formulas are used to measure the distance between the vectors in the algorithms: the Euclidean distance and k -Nearest neighborhood distance.to compare two methods. Keywords: Data mining, data mining algorithms, data mining applications
Author
Dr. Kelechi Churchill Onyejiaka
How to Cite
Kelechi Churchill Onyejiaka (Master Thesis). Unsupervised Learning Method Based on Partitioning in Data Mining, 2015, Eastern Mediterranean University, Department of Mathematics.
Keywords
License
Tüm Hakları Saklıdır
This work is shared under the specified license terms.
More theses from Eastern Mediterranean University
- An Investigation on Time and Cost Overrun in Construction Projects(2012)
- Radial Power-Law Position-dependent Mass, Cylindrical Coordinates, Spectral Signatures(2015)
- Deep Learning for Robotics(2020)
- Predicting performance level of reinforced concrete structures subject to corrosion as a function of time(2012)
- Some Results on Laguerre Type and Mittag-Leffler Type Functions(2017)
- Electrokinetic Treatment Technique for the Improvement of Soft Clayey Soils(2020)
