Machine Learning Modelling for Everyone


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Documentation for package ‘MLwrap’ version 0.1.0

Help Pages

build_model Create ML Model
fine_tuning Fine Tune ML Model
plot_calibration_curve Plotting Calibration Curve
plot_confusion_matrix Plotting Confusion Matrix
plot_distribution_by_class Plotting Output Distribution By Class
plot_gain_curve Plotting Gain Curve
plot_graph_nn Plot Neural Network Architecture
plot_integrated_gradients Plotting Integrated Gradients Plots
plot_lift_curve Plotting Lift Curve
plot_loss_curve Plot Neural Network Loss Curve
plot_olden Plotting Olden Values Barplot
plot_pfi Plotting Permutation Feature Importance Barplot
plot_pr_curve Plotting Precision-Recall Curve
plot_residuals_distribution Plotting Residuals Distribution
plot_roc_curve Plotting ROC Curve
plot_scatter_predictions Plotting Observed vs Predictions
plot_scatter_residuals Plotting Residuals vs Predictions
plot_shap Plotting SHAP Plots
plot_sobol_jansen Plotting Sobol-Jansen Values Barplot
plot_tuning_results Plotting Tuner Search Results
preprocessing Preprocessing Data Matrix
sensitivity_analysis Perform Sensitivity Analysis and Interpretable ML methods
sim_data sim_data
table_best_hyperparameters Best Hyperparameters Configuration
table_evaluation_results Evaluation Results
table_integrated_gradients_results Integrated Gradients Summarized Results Table
table_olden_results Olden Results Table
table_pfi_results Permutation Feature Importance Results Table
table_shap_results SHAP Summarized Results Table
table_sobol_jansen_results Sobol-Jansen Results Table