The International Arab Journal of Information Technology (IAJIT)


An Unsupervised Feed Forward Neural Network Method for Efficient Clustering

This paper presents a Real Unsupervised Feed Forward Neural Network (RUFFNN) clustering method with one epoch training and data dimensionality reduction ability to overcome some critical problems such as low training speed, low accuracy as well as high memory complexity in this area. The RUFFNN method trains a code book of real weights by utilizing input data directly without using any random values. The Best Match Weight (BMW) vector is mined from the weight codebook and consequently the Total Threshold (TT) of each input data is computed based on the BMW. Finally, the input data are clustered based on their exclusive TT. For evaluation purposes, the clustering performance of the RUFFNN was compared to several related clustering methods using various data sets. The accuracy of the RUFFNN was measured through the number of clusters and the quantity of Correctly Classified Nodes(CCN).The superior clustering accuracies of 96.63%, 96.67% and 59.36% were for the breast cancer, iris and spam datasets from the UCI repository respectively. The memory complexity of the proposed method was O( based on the number of nodes, attributes and size of the attribute.


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[23] Werbos P., Beyond Regression: New Tools for Prediction and Analysis in the Behavioral Sciences, Harvard University, 1974. Roya Asadi is a PhD of artificial intelligence (neural network) in computer science from the University of Malaya. Her interests include Artificial Neural Network modeling, Medical Informatics, Machine Learning, Data Mining, Image Processing. Mitra Asadi is a PhD candidate of Entrepreneurship Technology in Islamic Azad University- Central Tehran Branch, Iran. Her interests include: English Language Translation, Entrepreneurship Technology, and Management. Shokoofeh Asadi is Master of Agricultural Management Engineering from University of Science and research in Tehran- Iran. Her interests include: English Language Translation, Biological and Agricultural engineering, Management and leadership.