LogisticRegression scores

The datasets presented in this repository are obtained by applying the logistic regression (<i>LogisticRegression</i>) algorithm with the following specific hyperparameter setting and the different inputs that ,have been described in the journal paper: "<b>Data mining techniques for endometriosis detection in a data-scarce medical dataset</b>".HyperparametersC: 1Solver: liblinearmax_iter: 1000000Files<b>result_eb.csv</b>: Results for EB sample type.<b>result_ef.csv</b>: Results for EF sample type.<b>result_vagina.csv</b>: Results for vagina sample type.<b>result_oral.csv</b>: Results for oral sample type.<b>result_feces.csv</b>: Results for feces sample type.<b>result_frt.csv</b>: Results for FRT (EB + EF + vagina) sample type.<b>result_frt2.csv</b>: Results for FRT2 (EB + vagina) sample type.<b>properties_eb.log</b>: Arguments and result information for EB sample type (C, n_split, solver, max_iter, random_state, len_scores_before_filtering, len_scores_after_filtering, len_f1).<b>properties_ef.log</b>: Arguments and result information for EF sample type.<b>properties_vagina.log</b>: Arguments and result information for vagina sample type.<b>properties_oral.log</b>: Arguments and result information for oral sample type.<b>properties_feces.log</b>: Arguments and result information for feces sample type.<b>properties_frt.log</b>: Arguments and result information for FRT sample type.<b>properties_frt2.log</b>: Arguments and result information for FRT2 sample type.<br>

本仓库所呈现的数据集，系通过应用逻辑回归（LogisticRegression）算法，结合下述特定超参数配置，并采用期刊论文《面向稀缺医疗数据集的子宫内膜异位症检测的数据挖掘技术》中所述的不同输入生成。
超参数配置如下：
正则化系数C: 1；求解器solver: liblinear；最大迭代次数max_iter: 1000000
文件说明如下：
<b>result_eb.csv</b>：EB样本类型的实验结果。
<b>result_ef.csv</b>：EF样本类型的实验结果。
<b>result_vagina.csv</b>：阴道样本类型的实验结果。
<b>result_oral.csv</b>：口腔样本类型的实验结果。
<b>result_feces.csv</b>：粪便样本类型的实验结果。
<b>result_frt.csv</b>：FRT（EB + EF + 阴道）样本类型的实验结果。
<b>result_frt2.csv</b>：FRT2（EB + 阴道）样本类型的实验结果。
<b>properties_eb.log</b>：EB样本类型的参数与结果信息，包含C、划分折数n_split、求解器solver、最大迭代次数max_iter、随机状态random_state、过滤前得分长度len_scores_before_filtering、过滤后得分长度len_scores_after_filtering以及F1得分长度len_f1。
<b>properties_ef.log</b>：EF样本类型的参数与结果信息。
<b>properties_vagina.log</b>：阴道样本类型的参数与结果信息。
<b>properties_oral.log</b>：口腔样本类型的参数与结果信息。
<b>properties_feces.log</b>：粪便样本类型的参数与结果信息。
<b>properties_frt.log</b>：FRT样本类型的参数与结果信息。
<b>properties_frt2.log</b>：FRT2样本类型的参数与结果信息。