TY  - JOUR
T1  - An Analysis on K-Means Algorithm as an Imputation Method to Deal with Missing Values
AU - , B. Mehala AU - , K. Vivekanandan AU - , P. Ranjit Jeba Thangaiah 
JO  - Asian Journal of Information Technology
VL  - 7
IS  - 9
SP  - 434
EP  - 441
PY  - 2008
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2008.434.441
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2008.434.441
KW  - Missing values
KW  -imputation
KW  -preprocessing
KW  -data mining
AB  - Imputation is a class of procedures that aims to fill the missing values with estimated ones. This method involves replacing missing values with estimated ones based on some information available in the data set. There are many options varying from naive methods like mean or mode imputation to some learning methods like 4.5°C based on relationships among attributes. In this research the use of K-Means algorithm is analyzed as a new approach to treat missing values. This research is to evaluate the efficiency of K-Means imputation algorithm as an imputation method to treat missing data, comparing its performance with the performance obtained by Mean, Median, Mode and 4.5°C.
ER  -