## 4 Results
Table 4 shows the effectiveness of the blood hormones in normal, benign, and malignant subjects demonstrated through the use of performance assessment criteria such as precision, sensitivity, specificity, accuracy, and F1-score for the DT, SVM, and KNN classifiers using the t-SNE dimensionality reduction technique. After applying the t-SNE dimensionality reduction techniques to the KNN, SVM, and DT classifiers, the confusion matrix is shown in Figure 4 for identifying normal people, benign patients, and malignant patients from the blood levels of P, T, C, and HCG using statistical characteristics. In the diagonal, we see accurate recognition, whereas the off-diagonal areas represent substitution mistakes. Figure 4 depicts the proportion of correctly categorized data from the DT, SVM, and KNN classifiers by applying t-SNE to the blood level hormones. The accuracy of the DT was 93.3%, of the SVM was 86.7%, and of the KNN was 73.3%. Thus, the DT correctly identified 10 control patients, 10 benign patients, and 8 malignant patients, whereas 2 of the malignant patients were incorrectly classified as control healthy subjects. Figure 3: Confusion matrices for the DT, SVM and KNN classifiers using FA dimensionality reduction technique to demonstrate the blood hormones performance from the normal subjects, benign patients, and malignant patients. Table 5 shows the effectiveness of saliva hormones in normal subjects, benign patients, and malignant subjects demonstrated through the use of performance assessment criteria such as precision, sensitivity, specificity, accuracy, and F1-score for the DT, SVM, and KNN classifiers. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Classifiers** & **Parameters** & **Malignant** & **Benign** & **Control** & **Average** \\ \hline \multirow{2}{*}{DT} & precision & 100 & 100 & 83.3 & 94.4 \\ \cline{2-6}  & sensitivity & 80 & 100 & 100 & 93.3 \\ \cline{2-6}  & specificity & 100 & 100 & 90 & 96.7 \\ \cline{2-6}  & accuracy & 93.3 & 93.3 & 93.3 & 93.3 \\ \cline{2-6}  & F1-score & 88.9 & 100 & 90.9 & 93.3 \\ \hline \multirow{2}{*}{SVM} & precision & 100 & 81.8 & 80 & 87.3 \\ \cline{2-6}  & sensitivity & 90 & 90 & 80 & 86.7 \\ \cline{2-6}  & specificity & 100 & 90 & 90 & 93.3 \\ \cline{2-6}  & accuracy & 86.7 & 86.7 & 86.7 & 86.7 \\ \cline{2-6}  & F1-score & 94.7 & 85.7 & 80 & 86.8 \\ \hline \multirow{2}{*}{KNN} & precision & 80 & 77.8 & 63.6 & 73.8 \\ \cline{2-6}  & sensitivity & 80 & 70 & 70 & 73.3 \\ \cline{2-6}  & specificity & 90 & 90 & 80 & 86.7 \\ \cline{2-6}  & accuracy & 73.3 & 73.3 & 73.3 & 73.3 \\ \cline{2-6}  & F1-score & 80 & 73.7 & 66.7 & 73.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Performance evaluation, including precision, sensitivity, specificity, accuracy, and F1-score, for the DT, SVM, and KNN classifiers using the t-SNE dimensionality reduction technique to show the blood hormones performance from normal subjects, benign patients, and malignant patients. Figure 4: Confusion matrices for the DT, SVM, and KNN classifiers using the t-SNE dimensionality reduction technique to demonstrate the blood hormones performance from the normal subjects, benign patients, and malignant patients. The confusion matrix for identifying normal participants, benign patients, and malignant patients based on the salivary levels of P, T, C, and HCG is depicted in Figure 5, and it was created with statistical features and the KNN, SVM, and DT classifiers in that order. On the diagonal, the right recognition is seen, whereas the off-diagonal areas reflect the incorrect substitutions.