Man pages for tkolisnik/Rf2pval
A comprehensive approach to genomic analysis using scikit-learn's Random Forest models and rank-based feature reduction in R
| calculate_feature_importances | Calculate True and Permuted Feature Importances |
| calculate_full_set_pvalue | Calculate Proportion-Based P-Value for Entire Feature Set |
| calculate_quantiles | Calculate Quantiles of Feature Importance |
| calculate_ranked_based_pvalues | Calculate p-values for Each Feature Rank |
| calculate_SHAP_values | Calculate SHAP Values and Identify Significant Features |
| create_feature_matrix | Dataset Preparation Function for Scikit-Learn Random forest... |
| demo_rnaseq_data | Demo RNA-seq Dataset |
| fit_and_evaluate_rf | Fit and Evaluate Random Forest Model |
| generate_fi_rank_plot | Generate Feature Importance Score-Rank Plot |
| generate_pi_ECDF_plot | Generate ECDF Plot |
| generate_pi_histogram | Generate pi Histogram Plot |
| generate_shap_plots | Generate SHAP Plots |
| Rf2pval-package | Rf2pval: A comprehensive approach to genomic analysis using... |
| setup_python_pkgs | Centralized Setup for Python Environment |
| tune_and_train_rf_model | Perform hyperparameter tuning and training for... |
