SVC scores (rbf kernel and C=1)
收藏资源简介：
The datasets presented in this repository are obtained by applying the support vector classifier (SVC) 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: 1.0kernel: rbfmax_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, kernel, gamma, 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，系通过应用支持向量分类器（Support Vector Classifier, SVC）算法，结合下述特定超参数设置，并采用期刊论文《数据稀缺医疗数据集中子宫内膜异位症检测的数据挖掘技术》（原文标题：Data mining techniques for endometriosis detection in a data-scarce medical dataset）中所述的不同输入样本构建所得。 超参数设置如下： C: 1.0 核函数（kernel）: rbf 最大迭代次数（max_iter）: 1000000 附带文件说明如下： <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、核函数、gamma、最大迭代次数、随机种子random_state、过滤前得分数量、过滤后得分数量、F1得分数量） <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
