项目作者: TanerArslan

项目描述 :
Evaluating multiple classifiers after SVM-RFE (Support Vector Machine-Recursive Feature Elimination)
高级语言: Python
项目地址: git://github.com/TanerArslan/Benchmarking_Classifiers_after_SVM-RFE.git


Benchmarking_Classifiers_after_SVM-RFE

After SVM-RFE optimization and selecting the most important features (peptide-centric), following classifiers were trained using Monter-Carlo Cross-Validation (#100 iterations) and reported the accuracy score from validation dataset;

  • Random Forest

  • XGBoost

  • ExtraTree

  • Logistic Regression (L1, Ridge regression)

  • Logistic Regression (L2, LASSO)

  • SVM (Linear Kernel)

  • SVM (RBF Kernel)

  • Gaussian Naive Bayes

  • Bagging

Test accuracy results can be seen by PDF file.