TY - JOUR
ID -
TI - Modify Initialization k-means Clustering Algorithm to Generate Initial Centroids
AU - Lamia AbedNoor Muhammed لمياء عبدنور محمد
PY - 2014
VL - 6
IS - 2
SP - 176
EP - 185
JO - Journal of Al-Qadisiyah for Computer Science and Mathematics مجلة القادسية لعلوم الحاسوب والرياضيات
SN - 20740204 25213504
AB -
K-means is one of the most common clustering techniques used with numeric data. Different issues are conducted in k-means algorithm in order to reach the optimum solutions with best situations, weather producing good results or the ways used to produce the results efficiently. Initial centroids of this algorithm play important role, so the generation initial centroids attracting more work. However, this paper aims to discuss a new proposed step to improve the generation of initial centroids i.e. modification the first iteration of k-means algorithm. The experiment work of this paper would be applied with one of the famous data that is "iris", this data is suited with k-means algorithm. The experiments were tested with the origin k-means algorithm in two parameters: "execution time" and "cost function" that is represented by sum square error SSE. The results are promise work with this modification
ER -