TY - JOUR ID - TI - Text Classification Based on Weighted Extreme Learning Machine AU - PY - 2019 VL - 32 IS - 1 SP - 197 EP - 204 JO - Ibn Al-Haitham Journal For Pure and Applied Sciences مجلة ابن الهيثم للعلوم الصرفة والتطبيقية SN - 16094042 25213407 AB - The huge amount of documents in the internet led to the rapid need of text classification(TC). TC is used to organize these text documents. In this research paper, a new model isbased on Extreme Machine learning (EML) is used. The proposed model consists of manyphases including: preprocessing, feature extraction, Multiple Linear Regression (MLR) andELM. The basic idea of the proposed model is built upon the calculation of feature weights byusing MLR. These feature weights with the extracted features introduced as an input to theELM that produced weighted Extreme Learning Machine (WELM). The results showed agreat competence of the proposed WELM compared to the ELM.

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