Relevant-Based Feature Ranking (RBFR) Method for Text Classification Based on Machine Learning Algorithm
| العنوان: | Relevant-Based Feature Ranking (RBFR) Method for Text Classification Based on Machine Learning Algorithm |
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| المؤلفون: | V. Durga Prasad Jasti, Guttikonda Kranthi Kumar, M. Sandeep Kumar, V. Maheshwari, Prabhu Jayagopal, Bhaskar Pant, Alagar Karthick, M. Muhibbullah |
| المصدر: | Journal of Nanomaterials. 2022:1-12 |
| بيانات النشر: | Hindawi Limited, 2022. |
| سنة النشر: | 2022 |
| مصطلحات موضوعية: | Article Subject, General Materials Science |
| الوصف: | High dimensionality of the feature space is one of the problems in the field of text classification. Identification of optimal subset of features can optimize text classification process in terms of processing time and performance. In this paper, we propose a novel Relevant-Based Feature Ranking (RBFR) algorithm which identifies and selects smaller subsets of more relevant features in the feature space. We compared the performance of the RBFR against other existing feature selection methods such as balanced accuracy measure, information gain, Gini index, and odds ratio on 3 datasets, namely, 20 newsgroup, Reuters, and WAP datasets. We have used 5 machine learning models (SVM, NB, kNN, RF, and LR) to test and evaluate the proposed feature selection method. We found that the performance of the proposed feature selection method is 25.4305% times more effective than the existing feature selection methods in terms of accuracy. |
| وصف الملف: | text/xhtml |
| تدمد: | 1687-4129 1687-4110 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::143776b6e6e2b331e0fec14d1b7370c9 https://doi.org/10.1155/2022/9238968 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....143776b6e6e2b331e0fec14d1b7370c9 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 16874129 16874110 |
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