Fig 1.
Methodology and research design.
Table 1.
Results from the training and testing sets.
Table 2.
Statistical report on recommendation classification using logistic regression with count vectorizer.
Fig 2.
Confusion matrix of LR with count vectorizer.
Table 3.
Statistical Report on Recommendation Classification using Logistic Regression with TF-IDF Vectorizer.
Fig 3.
The confusion matrix of LR with TF-IDF vectorizer.
Table 4.
Statistical report on recommendation classification using naive Bayes with count vectorizer.
Fig 4.
The confusion matrix of Naive Bayes with count vectorizer.
Table 5.
Statistical report on recommendation classification using Naive Bayes with TF-IDF vectorizer.
Fig 5.
The confusion matrix of Naive Bayes with TF-IDF vectorization.
Table 6.
Statistical Report on Recommendation Classification using SVM with Count Vectorizer.
Fig 6.
The confusion matrix of SVM with count vectorization.
Table 7.
Statistical report on recommendation classification using SVM with TDF-IDF vectorizer.
Fig 7.
The confusion matrix of SVM with TF-IDF vectorization.
Table 8.
Statistical report on recommendation classification by random forest with count vectorizer.
Fig 8.
Confusion matrix of RF with count vectorizer.
Table 9.
Statistical report on recommendation classification by RF with TDF-IDF vectorizer.
Fig 9.
Confusion matrix of RF with TF-IDF Vectorizer.
Table 10.
Statistical report on recommendation classification using ada boosting with count vectorizer.
Fig 10.
The confusion matrix of ada boosting with count vectorizer.
Table 11.
Statistical report on recommendation classification via ada boosting with TDF-IDF vectorizer.
Fig 11.
The confusion matrix of ada boosting with TF-IDF vectorization.
Table 12.
Statistical report on recommendation classification using deep learning GRU.
Fig 12.
Precision-recall curve for the deep learning model GRU.
Table 13.
Statistical report on recommendation classification using bidirectional LSTM.
Fig 13.
The confusion matrix of LSTM.
Table 14.
Performance metrics of classifiers with count vectorizer.
Table 15.
Performance metrics of classifiers with TF-IDF vectorizer.