Jurnal
Two Text Classifiers in Online Discussion: Support Vector Machine vs Back-Propagation Neural Network
- Bagikan:
The purpose of this research is to compare the performance of two text classifiers; support vector
machine (SVM) and back-propagation neural network (BPNN) within categorize messages from an online
discussion. SVM has been recognized as one of the best algorithm for text categorization. BPNN is also a
popular categorization method that can handle linear and non linear problems and can achieve good
result. However, using SVM and BPNN in online discussion is rare. In this research, several SVM data are
trained in multi-class categorization to classify the same set with BPNN. The effectiveness of these two
text classifiers are measured and then statistically compared based on error rate, precision, recall and Fmeasure.
The experimental result shows that for text message categorization
in online discussion the performances of SVM outperform BPNN in term of error rate and precision; and falls behind BPNN in term of recall and F-measure.
Detail Information
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Jurnal
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Published
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| Departement | |
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| Bahasa |
Indonesia
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| Penerbit | TELKOMNIKA : Yogyakarta., 2014 |
| Edisi |
Published
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| Subyek | |
| No Panggil | |
| Copyright |
Universitas Ahmad Dahlan
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| Doi |