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Performance Evaluation of Multiple Classifiers for Predicting Fake News
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作者 Arzina Tasnim md. saiduzzaman +2 位作者 Mohammad Arafat Rahman Jesmin Akhter Abu Sayed md. Mostafizur Rahaman 《Journal of Computer and Communications》 2022年第9期1-21,共21页
The rise of fake news on social media has had a detrimental effect on society. Numerous performance evaluations on classifiers that can detect fake news have previously been undertaken by researchers in this area. To ... The rise of fake news on social media has had a detrimental effect on society. Numerous performance evaluations on classifiers that can detect fake news have previously been undertaken by researchers in this area. To assess their performance, we used 14 different classifiers in this study. Secondly, we looked at how soft voting and hard voting classifiers performed in a mixture of distinct individual classifiers. Finally, heuristics are used to create 9 models of stacking classifiers. The F1 score, prediction, recall, and accuracy have all been used to assess performance. Models 6 and 7 achieved the best accuracy of 96.13 while having a larger computational complexity. For benchmarking purposes, other individual classifiers are also tested. 展开更多
关键词 Fake News Machine Learning TF-IDF CLASSIFIER Estimator F1 Score RECALL Precision Voting Classifiers Stacking Classifier Soft Voting Hard Voting
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Comparison of Classical Method, Extension Principle and α-Cuts and Interval Arithmetic Method in Solving System of Fuzzy Linear Equations
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作者 Sahidul Islam md. saiduzzaman +1 位作者 md. Shafiqul Islam Abeda Sultana 《American Journal of Computational Mathematics》 2019年第1期1-24,共24页
The system of linear equations plays a vital role in real life problems such as optimization, economics, and engineering. The parameters of the system of linear equations are modeled by taking the experimental or obse... The system of linear equations plays a vital role in real life problems such as optimization, economics, and engineering. The parameters of the system of linear equations are modeled by taking the experimental or observation data. So the parameters of the system actually contain uncertainty rather than the crisp one. The uncertainties may be considered in term of interval or fuzzy numbers. In this paper, a detailed study of three solution techniques namely Classical Method, Extension Principle method and α-cuts and interval Arithmetic Method to solve the system of fuzzy linear equations has been done. Appropriate applications are given to illustrate each technique. Then we discuss the comparison of the different methods numerically and graphically. 展开更多
关键词 Fuzzy Set CLASSICAL Solution Extension Principle α-Cut and INTERVAL ARITHMETIC METHOD
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