The Effect of Ensemble Learning Models on Turkish Text Classification

Deniz Kılınç [1]

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The Effect of Ensemble Learning Models on Turkish Text Classification

Due to rapid development of the Internet and related technologies, the amount of text-based content generated through Internet applications is increasing from day to day. Since text-based content is unstructured, accessing and managing this data is almost impossible. Consequently, there is a need for automatic text classification process. Text mining is a discipline in the Data Mining field and offers algorithms in order to perform text classification. The main objective of text classification is forming a learning model by using a training data set with pre-defined categories and placing data with unknown categories into correct categories. Different text classification algorithms such as decision trees, Bayesian classifiers, rule-based classifiers, neural networks, k-nearest neighbor classifier, support vector machines and ensemble learning methods exist in the literature. In this study, the effect of ensemble learning models on Turkish text classification was evaluated. A publicly available data set named TTC-3600 which consists of 3600 news collected from 6 news portals was selected. Text classification process was performed on TTC-3600 data set by using 4 base classification algorithms Naïve Bayes, Support Vector Machine, K-Nearest Neighbor, J48 Decision tree and their Boosting, Bagging and Rotation Forest ensemble learning models. The experimental results shows that ensemble learning models generally give more accurate results by increasing the success of base classifiers.


Primary Language en
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Journal Section Articles
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Author: Deniz Kılınç

Bibtex @ { cbayarfbe254869, journal = {Celal Bayar University Journal of Science}, issn = {1305-130X}, eissn = {1305-1385}, address = {Celal Bayar University}, year = {2016}, volume = {12}, pages = {0 - }, doi = {10.18466/cbujos.04526}, title = {The Effect of Ensemble Learning Models on Turkish Text Classification}, key = {cite}, author = {Kılınç, Deniz} }
APA Kılınç, D . (2016). The Effect of Ensemble Learning Models on Turkish Text Classification. Celal Bayar University Journal of Science, 12 (2), . Retrieved from http://dergipark.org.tr/cbayarfbe/issue/23915/254869
MLA Kılınç, D . "The Effect of Ensemble Learning Models on Turkish Text Classification". Celal Bayar University Journal of Science 12 (2016): <http://dergipark.org.tr/cbayarfbe/issue/23915/254869>
Chicago Kılınç, D . "The Effect of Ensemble Learning Models on Turkish Text Classification". Celal Bayar University Journal of Science 12 (2016):
RIS TY - JOUR T1 - The Effect of Ensemble Learning Models on Turkish Text Classification AU - Deniz Kılınç Y1 - 2016 PY - 2016 N1 - DO - T2 - Celal Bayar University Journal of Science JF - Journal JO - JOR SP - 0 EP - VL - 12 IS - 2 SN - 1305-130X-1305-1385 M3 - UR - Y2 - 2019 ER -
EndNote %0 Celal Bayar University Journal of Science The Effect of Ensemble Learning Models on Turkish Text Classification %A Deniz Kılınç %T The Effect of Ensemble Learning Models on Turkish Text Classification %D 2016 %J Celal Bayar University Journal of Science %P 1305-130X-1305-1385 %V 12 %N 2 %R %U
ISNAD Kılınç, Deniz . "The Effect of Ensemble Learning Models on Turkish Text Classification". Celal Bayar University Journal of Science 12 / 2 (August 2016): 0-.