# Data Mining Techniques for Endometriosis Detection in a Data-Scarce Medical Dataset
## 2 Materials and Methods
### Dataset from Multiple Sample Types
The Jupyter notebooks with all the used code are available at 10.6084/m9.figshare.23905125. The results datasets that support the findings of this study and the figures of the scores are openly available in figshare at the following locations: LogisticRegression scores and figures: 10.6084/m9.figshare.23904903 and 10.6084/m9.figshare.24114696; DecisionTree scores and figures: 10.6084/m9.figshare.23904861 and 10.6084/m9.figshare.24114702; SVC scores and figures (linear kernel and C = 1): 10.6084/m9.figshare.2390493 and 10.6084/m9.figshare.24114687; SVC scores and figures (rbf kernel and C = 1): 10.6084/m9.figshare.24114681 and 10.6084/m9.figshare.24114579; SVC scores and figures (rbf kernel and C = 10): 10.6084/m9.figshare.23904954 and 10.6084/m9.figshare.24114570; SVC scores and figures (rbf kernel and C = 10): 10.6084/m9.figshare.23904972 and 10.6084/m9.figshare.24114561. **Conflicts of Interest:** The authors declare no conflicts of interest. The following abbreviations are used in this manuscript: \begin{tabular}{l l} ASVs & Amplicon Sequence Variants \\ CSV & Comma-Separated Values \\ DADA2 & Divisive Amplicon Denoising Algorithm 2 \\ EB & Endometi biopsy \\ EF & Endometi fluid \\ EM & Endometiosis \\ FRT & Female reproductive tract \\ GIT & Gastrointestinal tract \\ MRI & Magnetic Resonance Imaging \\ OTUs & Operational Taxonomic Units \\ RBF & Radial basis function \\ ROC & Receiver operating characteristic curve \\ rRNA & Ribosomal Ribonucleic Acid \\ SDK & Software Development Kit \\ SVC & Support vector classifier \\ SVM & Support vector machine \\ \end{tabular} 

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