Machine Learning Modelling for Everyone

Documentation for package ‘MLwrap’ version 0.1.0

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