Text classification based on weighted extreme learning machine

المؤلف

Salman, Haydar Mahmud

المصدر

Ibn al-Haitham Journal for Pure and Applied Science

العدد

المجلد 32، العدد 1 (30 إبريل/نيسان 2019)، ص ص. 197-204، 8ص.

الناشر

جامعة بغداد كلية التربية ابن الهيثم

تاريخ النشر

2019-04-30

دولة النشر

العراق

عدد الصفحات

8

التخصصات الرئيسية

الرياضيات
تكنولوجيا المعلومات وعلم الحاسوب

الموضوعات

الملخص EN

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 is based on extreme machine learning (EML) is used.

the proposed model consists of many phases including: preprocessing, feature extraction, multiple linear regression (MLR) and ELM.

the basic idea of the proposed model is built upon the calculation of feature weights by using MLR.

these feature weights with the extracted features introduced as an input to the ELM that produced weighted extreme learning machine (WELM).

the results showed a great competence of the proposed WELM compared to the ELM.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Salman, Haydar Mahmud. 2019. Text classification based on weighted extreme learning machine. Ibn al-Haitham Journal for Pure and Applied Science،Vol. 32, no. 1, pp.197-204.
https://search.emarefa.net/detail/BIM-898144

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Salman, Haydar Mahmud. Text classification based on weighted extreme learning machine. Ibn al-Haitham Journal for Pure and Applied Science Vol. 32, no. 1 (2019), pp.197-204.
https://search.emarefa.net/detail/BIM-898144

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Salman, Haydar Mahmud. Text classification based on weighted extreme learning machine. Ibn al-Haitham Journal for Pure and Applied Science. 2019. Vol. 32, no. 1, pp.197-204.
https://search.emarefa.net/detail/BIM-898144

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references : p. 204

رقم السجل

BIM-898144