Prediction Explanation with Dependence-Aware Shapley Values

aicc_full_cpp | AICc formula for several sets, alternative definition |

aicc_full_single_cpp | Temp-function for computing the full AICc with several X's... |

apply_dummies | Apply dummy variables - this is an internal function intended... |

check_features | Checks that two extracted feature lists have exactly the same... |

correction_matrix_cpp | correction term with trace_input in AICc formula |

create_ctree | Make all conditional inference trees |

explain | Explain the output of machine learning models with more... |

feature_combinations | Define feature combinations, and fetch additional information... |

feature_matrix_cpp | Get feature matrix |

gaussian_transform | Transforms a sample to standardized normal distribution |

gaussian_transform_separate | Transforms new data to standardized normal (dimension 1)... |

get_data_specs | Fetches feature information from a given data set |

get_list_approaches | Helper function used in 'explain.combined' |

get_model_specs | Fetches feature information from a given model object |

get_supported_models | Provides a data.table with the supported models |

hat_matrix_cpp | Computing single H matrix in AICc-function using the... |

inv_gaussian_transform | Transforms new data to a standardized normal distribution |

mahalanobis_distance_cpp | (Generalized) Mahalanobis distance |

make_dummies | Initiate the making of dummy variables |

model_checker | Check that the type of model is supported by the explanation... |

observation_impute | Generate permutations of training data using test... |

observation_impute_cpp | Get imputed data |

plot.shapr | Plot of the Shapley value explanations |

prediction | Calculate Shapley weights for test data |

predict_model | Generate predictions for different model classes |

prepare_data | Generate data used for predictions |

preprocess_data | Process (check and update) data according to specified... |

rss_cpp | sigma_hat_sq-function |

sample_combinations | Helper function to sample a combination of training and... |

sample_copula | Sample conditional variables using the Gaussian copula... |

sample_ctree | Sample ctree variables from a given conditional inference... |

sample_gaussian | Sample conditional Gaussian variables |

shapley_weights | Calculate Shapley weight |

shapr | Create an explainer object with Shapley weights for test... |

update_data | Updates data by reference according to the updater argument. |

weight_matrix | Calculate weighted matrix |

weight_matrix_cpp | Calculate weight matrix |

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