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Evaluating multiple classifiers after SVM-RFE (Support Vector Machine-Recursive Feature Elimination)

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TanerArslan/Benchmarking_Classifiers_after_SVM-RFE

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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.