OVERVIEW AND COMPARISON OF THREE CLASSIFIERS: ARABIC DOCUMENTS AS A CASE STUDY

Essam HANANDEH

doi:https://doi.org/10.17261/Pressacademia.2017.600

Makale detayları

OVERVIEW AND COMPARISON OF THREE CLASSIFIERS: ARABIC DOCUMENTS AS A CASE STUDY

Yazarlar:

Essam HANANDEH

Yayıncı:

PressAcademia

Ana Başlıklar:

Sosyal Bilimler

Dergi:

PressAcademia Procedia 2017 Vol.5 Issue 1, pp.274-277

Belge Tipi:

Makale

Yayın Tarihi:

6/2017

Belge Dili:

Türkçe

Document ID (Org No.):

2000776637

Sıklık:

Üç Yıllık

eISSN:

2459-0762

DOI:

https://doi.org/10.17261/Pressacademia.2017.600

Özet:

 


Nowadays,  text classification is
used in various fields of research and applications, such as information
retrieval, text mining, and data mining. This study tests the Naïve Bayes,
K-Nearest Neighbors, and Support Vector Machine algorithms on a relatively
large dataset of Arabic documents. This dataset comprise 1,000 Arabic documents
that are distributed across 10 classes. This comparison is based on recall and
precision measures. The evaluation results show that the Support Vector Machine
algorithms classifier outperforms the other two

.

Makale detayları

OVERVIEW AND COMPARISON OF THREE CLASSIFIERS: ARABIC DOCUMENTS AS A CASE STUDY

Yazarlar: Essam HANANDEH

Yayıncı: PressAcademia

Ana Başlıklar: Sosyal Bilimler

Dergi: PressAcademia Procedia 2017 Vol.5 Issue 1, pp.274-277

Belge Tipi: Makale

Yayın Tarihi: 6/2017

Belge Dili: Türkçe

Document ID (Org No.): 2000776637

Sıklık: Üç Yıllık

eISSN: 2459-0762

DOI: https://doi.org/10.17261/Pressacademia.2017.600

Sayı

Yazarlar:

Essam HANANDEH

Yayıncı:

PressAcademia

Ana Başlıklar:

Sosyal Bilimler

Dergi:

PressAcademia Procedia 2017 Vol.5 Issue 1, pp.274-277

Belge Tipi:

Makale

Yayın Tarihi:

6/2017

Belge Dili:

Türkçe

Document ID (Org No.):

2000776637

Sıklık:

Üç Yıllık

eISSN:

2459-0762

DOI:

https://doi.org/10.17261/Pressacademia.2017.600