Man pages for CoOL
Causes of Outcome Learning
| CoOL_0_binary_encode_exposure_data | Binary encode exposure data |
| CoOL_0_common_simulation | Common example |
| CoOL_0_complex_simulation | Complex example |
| CoOL_0_confounding_simulation | Confounding example |
| CoOL_0_mediation_simulation | Mediation example |
| CoOL_0_working_example | CoOL working example with sex, drug A, and drug B |
| CoOL_1_initiate_neural_network | Initiates a non-negative neural network |
| CoOL_2_train_neural_network | Training the non-negative neural network |
| CoOL_3_plot_neural_network | Plotting the non-negative neural network |
| CoOL_4_AUC | Plot the ROC AUC |
| CoOL_4_predict_risks | Predict the risk of the outcome using the fitted non-negative... |
| CoOL_5_layerwise_relevance_propagation | Layer-wise relevance propagation of the fitted non-negative... |
| CoOL_6_calibration_plot | Calibration curve |
| CoOL_6_dendrogram | Dendrogram and sub-groups |
| CoOL_6_individual_effects_matrix | Risk contribution matrix based on individual effects (had all... |
| CoOL_6_number_of_sub_groups | Number of subgroups |
| CoOL_6_sub_groups | Assign sub-groups |
| CoOL_6_sum_of_individual_effects | Predict the risk based on the sum of individual effects |
| CoOL_7_prevalence_and_mean_risk_plot | Prevalence and mean risk plot |
| CoOL_8_mean_risk_contributions_by_sub_group | Mean risk contributions by sub-groups |
| CoOL_9_visualised_mean_risk_contributions | Visualisation of the mean risk contributions by sub-groups |
| CoOL_9_visualised_mean_risk_contributions_legend | Legend to the visualisation of the mean risk contributions by... |
| CoOL_default | The default analysis for computational phase of CoOL |
| cpp_train_network_relu | Function used as part of other functions |
| random | Function used as part of other functions |
| rcpprelu | Function used as part of other functions |
| rcpprelu_neg | Function used as part of other functions |
| relu | Function used as part of other functions |
