Title :
Utilization of K-NN algorithm for expectation maximization based classification method
Author :
Aci, M. ; Inan, C. ; Avci, M.
Author_Institution :
Univ. of Cukurova, Adana
Abstract :
K nearest neighbor and Bayesian algorithms are effective methods of machine learning. In this work a data elimination approach is proposed to improve data clustering. The proposed method is based on hybridization of K nearest neighbor and Bayesian learning algorithms. The suggested method is tested on well-known machine learning data sets such as iris, wine and breast cancer and the results are concluded.
Keywords :
Bayes methods; expectation-maximisation algorithm; learning (artificial intelligence); Bayesian algorithms; K nearest neighbor algorithms; K-NN algorithm; data clustering; data elimination approach; expectation maximization based classification method; machine learning; Bayesian methods; Clustering algorithms; Gaussian distribution; Iris; Learning systems; Machine learning; Machine learning algorithms; Nearest neighbor searches; Probability distribution; Telephony; Bayesian algorithm; classification; hybrid method; k nearest neighbor;
Conference_Titel :
Intelligent Systems, 2008. IS '08. 4th International IEEE Conference
Conference_Location :
Varna
Print_ISBN :
978-1-4244-1739-1
Electronic_ISBN :
978-1-4244-1740-7
DOI :
10.1109/IS.2008.4670463
