Title: Comparison of Clustering Algorithms with Feature Selection on Breast Cancer dataset
Publisher: Guru Nanak Publications
Series: Volume 5 Issue 1
Authors: M. V. Anjana Devi, Dr. D. D. Sarma
When compared to all other cancers in
developing countries Breast Cancer is the primary
cause of death in women. As per the statistics of
National Cancer institute, Breast Cancer is the second
most common cause in women in developed countries.
The Breast cancer risk is one in twenty eight women.
Data clustering is a process of putting similar
data into clusters. Clustering algorithms partition a
dataset into a fixed number of clusters supplied by the
user. Here Data mining clustering algorithms are used
to compare the performance of major clustering
algorithms. The Breast Cancer dataset taken from UCI
machine learning repository to analyze An experiment
was conducted with data mining tool using three
algorithms viz., k-means clustering, Hierarchical
clustering and Density based clustering on the
Wisconsin's dataset on Breast cancer. The results are
analysed using principal component filter.
Download Full Text
(For complimentary copy, please contact Chief_editor@innovationjournals.com)