Efficient English text classification using selected Machine Learning Techniques
Text classification (TC) is an approach used for the classification of any kind of documents for the target category or out. In this paper, we implemented the Support Vector Machines (SVM) model in classifying English text and documents. Here we did two analytical experiments to check the selected c...
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| Format: | Article |
| Language: | English |
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Elsevier
2021-06-01
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| Series: | Alexandria Engineering Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016821000806 |
| Summary: | Text classification (TC) is an approach used for the classification of any kind of documents for the target category or out. In this paper, we implemented the Support Vector Machines (SVM) model in classifying English text and documents. Here we did two analytical experiments to check the selected classifiers using English documents. Experimental results performed on a set of 1033 text document present that the Rocchio classifier provides the best performance results when the size of the feature set is small while SVM outperforms the other classifiers. From the experimental analysis, we observed that the classification rate exceeds 90% when using more than 4000 features. |
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| ISSN: | 1110-0168 |