| | Ref. | Algorithms | Dataset | Evaluation parameter(s) | Performance |
| | [6] | DMNBText, Liblinear, NB, J48 | 1463 Roman Urdu tweets | Accuracy, ROC-AUC | Obtained Max accuracy 95.42% using DMNB | | [7] | K-Means clustering | 200 spam-based emails | Accuracy, recall | They obtained 98.42% accuracy | | [8] | NB, SVM | English and Malay emails | Accuracy | Max accuracy achieved is 86.40% | | [9] | Hybrid bagging, Approach, NB, J48 | 1000 Spam base emails | Accuracy, Precision, recall, F-Measure | HB approach has obtained max accuracy | | [1] | AdaBoost bagging, SVM, KNN, RF | 5573 emails dataset | Accuracy | Max accuracy achieved is 98% | | [10] | Boosting, bagging, KNN, SVM, RF, ensemble | 5674 labelled dataset | Accuracy, precision, recall, F-measure | Max accuracy achieved is 97.5% using SVM | | [11] | Integrated NB, PSO | Spam base emails dataset | Accuracy, precision, recall, F-measure | Max accuracy achieved is 95.5% using INB |
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