# Data Mining Techniques for Endometriosis Detection in a Data-Scarce Medical Dataset
## 2 Materials and Methods
### Dataset from Multiple Sample Types
In particular, the result obtained in the oral region is very promising. ### Decision Tree Classification

The main parameters for this classification are shown in Table 17. Table 18 summarizes the main findings of this experiment using these parameters. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Metric** & **Statistic** & **EB** & **EF** & **Vaginal** & **Oral** & **Fecal** & **FRT** & **FRT2** \\ \hline \multirow{4}{*}{Accuracy} & \multirow{4}{*}{\(\Big{\{}}\)} & \# & 536 & 469 & 625 & 179 & 335 & 610 & 608 \\  & & & & & & & & \\  & & & & & & & & \\ \multirow{4}{*}{Precision} & \multirow{4}{*}{\(\Big{\{}}\)} & \(\overline{X}(\%)\) & 38.43 & 37.67 & 29.97 & 80.07 & 59.38 & 39.78 & 46.38 \\  & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\ \multirow{4}{*}{Recall} & \multirow{4}{*}{\(\Big{\{}}\)} & \(\overline{X}(\%)\) & 23.54 & 22.28 & 20.27 & 71.97 & 40.72 & 30.16 & 35.8 \\  & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\ \multirow{4}{*}{F1} & \multirow{4}{*}{\(\Big{\{}}\)} & \(\overline{X}(\%)\) & 36.29 & 33.48 & 38.8 & 81.01 & 69.25 & 54.75 & 61.84 \\  & & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\ \hline \multirow{4}{*}{F1} & \multirow{4}{*}{\(\Big{\{}}\)} & \# & 215 & 175 & 267 & 145 & 232 & 360 & 398 \\  & & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 16: Global mean (\(\overline{X}\)) and global standard deviation (\(\sigma\)) for scores for logistic regression classification. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Name** & **Value** & **Description** \\ \hline Classifier & DecisionTreeClassifier & The Python classifier from sklearn.tree. \\  & & The number of features to consider when looking \\ max\_features & sqrt & for the best split: this parameter affected the \\  & & & performance and complexity of the decision tree. \\ n\_repeats & 100 & The number of repetitions in RepeatedK Fold. \\ \hline \hline \end{tabular}
\end{table} 
Table 17: The parameters for the decision tree regression classification model. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Metric** & **Statistic** & **EB** & **EF** & **Vaginal** & **Oral** & **Fecal** & **FRT** & **FRT2** \\ \hline \multirow{4}{*}{Accuracy} & \multirow{4}{*}{\(\Big{\{}}\)} & \# & 536 & 469 & 625 & 179 & 335 & 610 & 608 \\  & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\ \multirow{4}{*}{Precision} & \multirow{4}{*}{\(\Big{\}}\)} & \(\overline{X}(\%)\) & 38.43 & 37.67 & 29.97 & 80.07 & 59.38 & 39.78 & 46.38 \\  & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\  & & & & & & & \\ \multirow{4}{*}{Precision} & \(\Big{\{}}\)} & 205 & 112 & 160 & 143 & 148 & 356 & 294 \\  & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\  & & & & & & & \\  & & & & & & & & \\ \hline \hline \end{tabular} \# denotes the number of classifiers used in the calculation of the statistics.

\end{table} 
Table 18: Global mean (\(\overline{X}\)) and global standard deviation (\(\sigma\)) for scores for decision tree classification. Table 18 shows that the random classifiers for the EF and vaginal samples had F1 scores below 33.3%, which is the minimum threshold given by Equation (14). This value suggests that they performed more poorly than the random classifier. ### Support Vector Classification with the linear kernel

The main parameters for this classification are shown in Table 19. Table 20 summarizes the main findings of this experiment using the listed parameters. The results of the SVC with the linear kernel shown in Table 20 are very similar to those obtained with logistic regression. Therefore, the results support the initial hypothesis that the classification in the oral and fecal regions is better than in the reproductive region.