Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
Text classification refers to the problem of classifying text documents into one class or more from a set of predefined categories. Text classification is significant part of “text mining”. In addition, the text classification problem has become the focus of researchers because of its great importance applications in organizing large input data. Many successful algorithms applied to the text categorization. In this research, we are trying to improve performance and increase the accuracy of the results by applying the “Singular Value Decomposition” (SVD) mechanism in order to minimize the dimension of input attributes and “Feature selection” approach to choose the features that hold enough information to help in the classification task. This classification has been done by using back propagation neural network.
How to cite this article:
Yaqeen Saad and Khalid Shaker. Dimension Reduction Techniques for Document Categorization with
Back Propagation Neural Network.
DOI: https://doi.org/10.36478/jeasci.2018.1304.1309
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2018.1304.1309