Index

_

__call__() (GaussianProcessAdd_Mechanism method) (GaussianProcessMix_Mechanism method) (LinearMechanism method) (Polynomial_Mechanism method) (SigmoidAM_Mechanism method) (SigmoidMix_Mechanism method) __contains__() (Independencies method) __init__() (AcyclicGraphGenerator method) (BaseExperiment method) (BaseModel method) (BootstrapResult method) (CAM method) (ColumnsDataset method) (ConditionalIndependencies method) (DAG method) (DecomposableScore method) (DFF method) (DirectLiNGAM method) (Experiment method) (FCI method) (GaussianProcessAdd_Mechanism method) (GaussianProcessMix_Mechanism method) (GaussObsL0Pen method) (GBTRegressor method), [1] (GES method) (GraphDiscovery method), [1] (GraphIndependence method) (Hierarchies method) (HSIC method) (HSIC_Values method) (IndependenceAssertion method) (Independencies method) (Knowledge method), [1] (LBFGSBScipy method) (LinearMechanism method) (LocallyConnected method) (MDN method) (Metrics method) (MLP method) (MLP.Block method) (MLPModel method) (MMDLoss method) (NNRegressor method), [1] (NOTEARS method) (PC method) (PDAG method) (PermutationImportance method) (Polynomial_Mechanism method) (RBF method) (RegQuality method) (Rex method), [1] (ShapDiscrepancy method) (ShapEstimator method) (SigmoidAM_Mechanism method) (SigmoidMix_Mechanism method) (StructureEstimator method) (SufficientSets method)

__repr__() (ConditionalIndependencies method), [1] __str__() (ConditionalIndependencies method) (SufficientSets method), [1] _cache (ConditionalIndependencies attribute) (SufficientSets attribute)

A

active_trail_nodes() (DAG method) AcyclicGraphGenerator (class in causalexplain.generators.generators) add() (ConditionalIndependencies method), [1] (SufficientSets method), [1] add_assertions() (Independencies method) add_edge() (DAG method) add_edges_from() (DAG method) add_grid() (in module causalexplain.common.plot) add_node() (DAG method)

add_nodes_from() (DAG method) add_noise() (MDN static method) adj() (in module causalexplain.estimators.ges.utils) adjacency_matrices_ (BootstrapResult property) adjust() (ShapEstimator method) all_columns (BaseModel attribute) allDagsIntern() (in module causalexplain.metrics.SID) allDagsJonas() (in module causalexplain.metrics.SID) aupr (Metrics attribute)

B

backward() (TraceExpm static method) backward_step() (GES method), [1] BaseExperiment (class in causalexplain.common.notebook) BaseModel (class in causalexplain.models._models) bias (LocallyConnected attribute) bootstrap() (BootstrapMixin method) (Rex method), [1]

BootstrapMixin (class in causalexplain.estimators.lingam.bootstrap) BootstrapResult (class in causalexplain.estimators.lingam.bootstrap) break_cycles() (Rex method), [1] break_cycles_if_present() (in module causalexplain.common.utils) break_cycles_using_prior() (in module causalexplain.common.utils) build_skeleton() (PC method)

C

callbacks (BaseModel attribute) CAM (class in causalexplain.estimators.cam.cam) cartesian() (in module causalexplain.estimators.ges.utils) cast_categoricals_to_int() (in module causalexplain.common.utils) causalexplain module causalexplain._version module causalexplain.causalexplainer module causalexplain.common module causalexplain.common.metrics_config module causalexplain.common.notebook module causalexplain.common.plot module causalexplain.common.utils module causalexplain.estimators module causalexplain.estimators.cam module causalexplain.estimators.cam.cam module causalexplain.estimators.cam.computeScoreMat module causalexplain.estimators.cam.computeScoreMatParallel module causalexplain.estimators.cam.pruning module causalexplain.estimators.cam.selGam module causalexplain.estimators.cam.selGamBoost module causalexplain.estimators.cam.selLasso module causalexplain.estimators.cam.selLm module causalexplain.estimators.cam.train_gam module causalexplain.estimators.cam.train_GAMboost module causalexplain.estimators.cam.train_gp module causalexplain.estimators.cam.train_lasso module causalexplain.estimators.cam.train_linear module causalexplain.estimators.cam.train_LMboost module causalexplain.estimators.cam.updateScoreMat module causalexplain.estimators.fci module causalexplain.estimators.fci.fci module causalexplain.estimators.ges module causalexplain.estimators.ges.decomposable_score module causalexplain.estimators.ges.ges module causalexplain.estimators.ges.scores module causalexplain.estimators.ges.utils module causalexplain.estimators.lingam module causalexplain.estimators.lingam.base module causalexplain.estimators.lingam.bootstrap module causalexplain.estimators.lingam.lingam module causalexplain.estimators.lingam.utils module causalexplain.estimators.notears module causalexplain.estimators.notears.lbfgsb_scipy module causalexplain.estimators.notears.linear module causalexplain.estimators.notears.locally_connected module causalexplain.estimators.notears.loss module causalexplain.estimators.notears.main module causalexplain.estimators.notears.notears module causalexplain.estimators.notears.trace_expm module causalexplain.estimators.notears.utils module causalexplain.estimators.pc module causalexplain.estimators.pc.ci_tests module causalexplain.estimators.pc.dag module causalexplain.estimators.pc.estimators module causalexplain.estimators.pc.independencies module causalexplain.estimators.pc.pc module causalexplain.estimators.pc.pdag module

causalexplain.estimators.rex module causalexplain.estimators.rex.knowledge module causalexplain.estimators.rex.rex module causalexplain.explainability module causalexplain.explainability.hierarchies module causalexplain.explainability.perm_importance module causalexplain.explainability.regression_quality module causalexplain.explainability.shapley module causalexplain.generators module causalexplain.generators.generators module causalexplain.generators.mechanisms module causalexplain.independence module causalexplain.independence.cond_indep module causalexplain.independence.edge_orientation module causalexplain.independence.effect module causalexplain.independence.feature_selection module causalexplain.independence.graph_independence module causalexplain.independence.hsic module causalexplain.independence.kernels module causalexplain.independence.mic module causalexplain.independence.regressors module causalexplain.metrics module causalexplain.metrics.compare_graphs module causalexplain.metrics.SID module causalexplain.models module causalexplain.models._base_models module causalexplain.models._columnar module causalexplain.models._loss module causalexplain.models._models module causalexplain.models._weight_utils module causalexplain.models.dnn module causalexplain.models.gbt module ch() (in module causalexplain.estimators.ges.utils) chain_component() (in module causalexplain.estimators.ges.utils) chi_square() (in module causalexplain.estimators.pc.ci_tests) cleanup_graph() (in module causalexplain.common.plot) closure() (Independencies method) columns (BaseModel attribute) ColumnsDataset (class in causalexplain.models._columnar) combine_and_evaluate_dags() (GraphDiscovery method), [1] combine_dags() (in module causalexplain.common.utils) combined_metrics() (in module causalexplain.common.plot) common_step() (MDN method) compare_graphs_precision() (in module causalexplain.estimators.notears.utils) compare_graphs_recall() (in module causalexplain.estimators.notears.utils) compare_graphs_specificity() (in module causalexplain.estimators.notears.utils) compare_graphs_undirected() (in module causalexplain.estimators.notears.utils) complete_samples_only (StructureEstimator attribute) compute_caus_order() (in module causalexplain.metrics.SID) compute_cond_indep_pvals() (GraphIndependence method) compute_correlated_features() (Hierarchies static method) compute_correlation_matrix() (Hierarchies static method) compute_error_contribution() (ShapEstimator method) compute_regression_quality() (Rex method), [1] computeGaussKernel() (in module causalexplain.generators.mechanisms) computePathMatrix() (in module causalexplain.metrics.SID) computePathMatrix2() (in module causalexplain.metrics.SID) computeScoreMat() (in module causalexplain.estimators.cam.computeScoreMat) computeScoreMatParallel() (in module causalexplain.estimators.cam.computeScoreMatParallel) ConditionalIndependencies (class in causalexplain.independence.cond_indep) configure_optimizers() (DFF method) (MDN method) (MLP method) connect_hierarchies() (in module causalexplain.explainability.hierarchies) connect_isolated_nodes() (in module causalexplain.explainability.hierarchies) contains() (Independencies method) convert_args_tuple() (in module causalexplain.estimators.pc.estimators) copy() (PDAG method) correct_edge_from_prior() (in module causalexplain.common.utils) correlation_matrix() (in module causalexplain.common.plot) correlation_th (ShapEstimator attribute) correlations (Hierarchies attribute) count_accuracy() (in module causalexplain.estimators.notears.utils) create_estimator() (BaseExperiment method) create_experiments() (GraphDiscovery method), [1] custom_main() (in module causalexplain.explainability.shapley) (in module causalexplain.independence.cond_indep) (in module causalexplain.models.dnn) (in module causalexplain.models.gbt)

D

DAG (class in causalexplain.estimators.pc.dag) dag (DirectLiNGAM attribute) (GES attribute), [1] (PC attribute) (Rex attribute), [1] dag() (in module causalexplain.common.plot) dag2cpdagAdj() (in module causalexplain.metrics.SID) dag2dot() (in module causalexplain.common.plot) dag_main() (in module causalexplain.independence.cond_indep) dag_to_cpdag() (in module causalexplain.estimators.ges.utils) dags() (in module causalexplain.common.plot) data (StructureEstimator attribute) debug (GES attribute) debug_() (in module causalexplain.metrics.SID)

DecomposableScore (class in causalexplain.estimators.ges.decomposable_score) delete() (in module causalexplain.estimators.ges.utils) delete_operator() (GES method) deprecated_dags() (in module causalexplain.common.plot) device (BaseModel attribute) (MLP attribute) (PermutationImportance attribute) (ShapEstimator attribute) DFF (class in causalexplain.models._base_models) digraph_from_connected_features() (in module causalexplain.common.utils) DirectLiNGAM (class in causalexplain.estimators.lingam.lingam) do() (DAG method) draw_graph_subplot() (in module causalexplain.common.plot) dSepAdji() (in module causalexplain.metrics.SID)

E

entails() (Independencies method) estimate() (in module causalexplain.independence.effect) estimate_edge() (in module causalexplain.independence.effect) estimator_name (Experiment attribute) evaluate_graph() (in module causalexplain.metrics.compare_graphs) exhaustive (ShapEstimator attribute) expand_clusters_perm_importance() (Hierarchies method)

Experiment (class in causalexplain.common.notebook) experiment_exists() (BaseExperiment method) explainer (ShapEstimator attribute) export() (GraphDiscovery method), [1] extra_repr() (LocallyConnected method) extra_trainer_args (BaseModel attribute) extract_weights() (in module causalexplain.models._weight_utils)

F

f1 (Metrics attribute) FCI (class in causalexplain.estimators.fci.fci) feature_names (DirectLiNGAM attribute) (GES attribute) (Rex attribute), [1] filter_causes_only() (FCI method) find_all_paths() (in module causalexplain.estimators.lingam.utils) find_cluster_change_point() (in module causalexplain.independence.feature_selection) find_colliders_in_path() (in module causalexplain.independence.cond_indep) find_crossing_point() (in module causalexplain.common.utils) fit() (CAM method) (DirectLiNGAM method) (Experiment method), [1] (GBTRegressor method), [1] (GES method), [1] (GraphIndependence method) (Hierarchies method) (HSIC method) (NNRegressor method), [1] (NOTEARS method) (PC method) (PermutationImportance method) (Rex method), [1] (ShapEstimator method) fit_and_get_residuals() (in module causalexplain.independence.regressors)

fit_bic() (GES method), [1] fit_experiments() (GraphDiscovery method), [1] fit_predict() (CAM method) (DirectLiNGAM method) (Experiment method) (FCI method) (GES method) (GraphIndependence method) (NOTEARS method) (PC method) (PermutationImportance method) (Rex method), [1] Fn (Metrics attribute) format_graph() (in module causalexplain.common.plot) format_time() (in module causalexplain.common.utils) forward() (DFF method) (LocallyConnected method) (MDN method) (MLP method) (MLP.Block method) (MMDLoss method) (RBF method) (TraceExpm static method) forward_step() (GES method), [1] Fp (Metrics attribute) full_score() (GaussObsL0Pen method)

G

G_final (Rex attribute), [1] g_sample() (MDN static method) gaussian_cause() (in module causalexplain.generators.mechanisms) gaussian_probability() (MDN static method) GaussianProcessAdd_Mechanism (class in causalexplain.generators.mechanisms) GaussianProcessMix_Mechanism (class in causalexplain.generators.mechanisms) GaussObsL0Pen (class in causalexplain.estimators.ges.scores) GBTRegressor (class in causalexplain.models) (class in causalexplain.models.gbt) generate() (AcyclicGraphGenerator method) generate_random_dag() (in module causalexplain.estimators.notears.utils) GES (class in causalexplain.estimators.ges.ges) ges_adjmat (GES attribute), [1] ges_score (GES attribute), [1] get_all_variables() (Independencies method) get_ancestral_graph() (DAG method) get_assertion() (IndependenceAssertion method) get_assertions() (Independencies method) get_backdoor_paths() (in module causalexplain.independence.cond_indep) get_bandwidth() (RBF method) get_causal_direction_counts() (BootstrapResult method) get_children() (DAG method) get_conditional_independencies() (in module causalexplain.independence.cond_indep) get_directed_acyclic_graph_counts() (BootstrapResult method) get_edge_orientation() (in module causalexplain.independence.edge_orientation) get_factorized_product() (Independencies method) get_feature_names() (in module causalexplain.common.utils) get_feature_types() (in module causalexplain.common.utils)

get_immoralities() (DAG method) get_independencies() (DAG method) get_indInAllOthers() (in module causalexplain.metrics.SID) get_leaves() (DAG method) get_markov_blanket() (DAG method) get_parents() (DAG method) get_paths() (BootstrapResult method) (in module causalexplain.independence.cond_indep) get_prior_from_ref_graph() (Rex method), [1] get_probabilities() (BootstrapResult method) get_random() (DAG static method) get_roots() (DAG method) get_sufficient_sets() (in module causalexplain.independence.cond_indep) get_sufficient_sets_for_pair() (in module causalexplain.independence.cond_indep) get_total_causal_effects() (BootstrapResult method) gmm_cause() (in module causalexplain.generators.mechanisms) graph_from_adjacency() (in module causalexplain.common.utils) graph_from_adjacency_file() (in module causalexplain.common.utils) graph_from_dictionary() (in module causalexplain.common.utils) graph_from_dot_file() (in module causalexplain.common.utils) graph_intersection() (in module causalexplain.common.utils) graph_to_adjacency() (in module causalexplain.common.utils) graph_to_adjacency_file() (in module causalexplain.common.utils) graph_to_dot_file() (in module causalexplain.common.utils) graph_union() (in module causalexplain.common.utils) GraphDiscovery (class in causalexplain) (class in causalexplain.causalexplainer) GraphIndependence (class in causalexplain.independence.graph_independence)

H

hammingDist() (in module causalexplain.metrics.SID) hierarchical_dissimilarities() (Hierarchies method) Hierarchies (class in causalexplain.explainability.hierarchies) hierarchies (Rex attribute), [1] hierarchies() (in module causalexplain.common.plot)

hpo_n_trials (Rex attribute), [1] HSIC (class in causalexplain.independence.hsic) hsic (HSIC property) (HSIC_Values attribute) HSIC_Values (class in causalexplain.independence.hsic)

I

identify_relationships() (in module causalexplain.models._weight_utils) in_degree_iter() (DAG method) indep (Rex attribute), [1] independence (HSIC property) (HSIC_Values attribute) IndependenceAssertion (class in causalexplain.estimators.pc.independencies) Independencies (class in causalexplain.estimators.pc.independencies) induced_subgraph() (in module causalexplain.estimators.ges.utils) infer_causal_relationships() (in module causalexplain.models._weight_utils) info() (Knowledge method), [1] init_callbacks() (BaseModel method) init_data() (BaseModel method) init_logger() (BaseModel method) init_variables() (AcyclicGraphGenerator method)

insert() (GES method) is_clique() (in module causalexplain.estimators.ges.utils) is_consistent_extension() (in module causalexplain.estimators.ges.utils) is_dag() (in module causalexplain.estimators.ges.utils) (in module causalexplain.estimators.notears.utils) is_dconnected() (DAG method) is_equivalent() (Independencies method) is_fitted_ (DirectLiNGAM attribute) (GES attribute) (PC attribute) (Rex attribute), [1] is_iequivalent() (DAG method) iterate (GES attribute), [1] iterative_predict() (Rex method), [1] iters (ShapEstimator attribute)

K

kernel_Delta() (in module causalexplain.independence.kernels) kernel_Delta_norm() (in module causalexplain.independence.kernels) kernel_Gaussian() (in module causalexplain.independence.kernels)

Knowledge (class in causalexplain.estimators.rex) (class in causalexplain.estimators.rex.knowledge) ks_pvalue (ShapDiscrepancy attribute) ks_result (ShapDiscrepancy attribute)

L

label_edges() (in module causalexplain.estimators.ges.utils) latex_string() (IndependenceAssertion method) (Independencies method) latex_table_by_datatype() (in module causalexplain.common.plot) latex_table_by_method() (in module causalexplain.common.plot) layer_weights() (in module causalexplain.models._weight_utils) LBFGSBScipy (class in causalexplain.estimators.notears.lbfgsb_scipy) least_squares_loss() (in module causalexplain.estimators.notears.loss) least_squares_loss_cov() (in module causalexplain.estimators.notears.loss) least_squares_loss_cov_grad() (in module causalexplain.estimators.notears.loss)

least_squares_loss_grad() (in module causalexplain.estimators.notears.loss) LinearMechanism (class in causalexplain.generators.mechanisms) linkage_mat (Hierarchies attribute) list_files() (in module causalexplain.common.utils) load() (Experiment method), [1] (GraphDiscovery method), [1] load_experiment() (in module causalexplain.common.utils) local_independencies() (DAG method) local_score() (DecomposableScore method) LocallyConnected (class in causalexplain.estimators.notears.locally_connected) logger (BaseModel attribute)

M

main() (in module causalexplain.estimators.cam.cam) (in module causalexplain.estimators.fci.fci) (in module causalexplain.estimators.ges.ges) (in module causalexplain.estimators.lingam.lingam) (in module causalexplain.estimators.notears.lbfgsb_scipy) (in module causalexplain.estimators.notears.locally_connected) (in module causalexplain.estimators.notears.notears) (in module causalexplain.estimators.notears.trace_expm) (in module causalexplain.estimators.pc.pc) (in module causalexplain.estimators.rex.rex) (in module causalexplain.independence.cond_indep) (in module causalexplain.independence.effect) (in module causalexplain.independence.feature_selection) (in module causalexplain.metrics.SID) matplotlib_repr() (Metrics method) MDN (class in causalexplain.models._base_models) mdn_loss() (MDN method) mean_shap_percentile (ShapEstimator attribute) mechanism() (GaussianProcessAdd_Mechanism method) (GaussianProcessMix_Mechanism method) (Polynomial_Mechanism method) (SigmoidAM_Mechanism method) (SigmoidMix_Mechanism method) member() (in module causalexplain.estimators.ges.utils) Metrics (class in causalexplain.metrics.compare_graphs) metrics (DirectLiNGAM attribute) (GES attribute) (PC attribute) min_impact (ShapEstimator attribute) minimal_dseparator() (DAG method) MLP (class in causalexplain.models._base_models) MLP.Block (class in causalexplain.models._base_models) MLPModel (class in causalexplain.models._models) mmd_loss() (MDN static method) MMDLoss (class in causalexplain.models._loss) model (BaseModel attribute) (GraphDiscovery property), [1] models (Rex attribute), [1] (ShapEstimator attribute) module causalexplain causalexplain._version causalexplain.causalexplainer causalexplain.common causalexplain.common.metrics_config causalexplain.common.notebook causalexplain.common.plot causalexplain.common.utils causalexplain.estimators causalexplain.estimators.cam causalexplain.estimators.cam.cam causalexplain.estimators.cam.computeScoreMat causalexplain.estimators.cam.computeScoreMatParallel causalexplain.estimators.cam.pruning causalexplain.estimators.cam.selGam causalexplain.estimators.cam.selGamBoost causalexplain.estimators.cam.selLasso causalexplain.estimators.cam.selLm causalexplain.estimators.cam.train_gam causalexplain.estimators.cam.train_GAMboost causalexplain.estimators.cam.train_gp causalexplain.estimators.cam.train_lasso causalexplain.estimators.cam.train_linear causalexplain.estimators.cam.train_LMboost causalexplain.estimators.cam.updateScoreMat causalexplain.estimators.fci causalexplain.estimators.fci.fci causalexplain.estimators.ges causalexplain.estimators.ges.decomposable_score causalexplain.estimators.ges.ges causalexplain.estimators.ges.scores causalexplain.estimators.ges.utils causalexplain.estimators.lingam causalexplain.estimators.lingam.base causalexplain.estimators.lingam.bootstrap causalexplain.estimators.lingam.lingam causalexplain.estimators.lingam.utils causalexplain.estimators.notears causalexplain.estimators.notears.lbfgsb_scipy causalexplain.estimators.notears.linear causalexplain.estimators.notears.locally_connected causalexplain.estimators.notears.loss causalexplain.estimators.notears.main causalexplain.estimators.notears.notears causalexplain.estimators.notears.trace_expm causalexplain.estimators.notears.utils causalexplain.estimators.pc causalexplain.estimators.pc.ci_tests causalexplain.estimators.pc.dag causalexplain.estimators.pc.estimators causalexplain.estimators.pc.independencies causalexplain.estimators.pc.pc causalexplain.estimators.pc.pdag causalexplain.estimators.rex causalexplain.estimators.rex.knowledge causalexplain.estimators.rex.rex causalexplain.explainability causalexplain.explainability.hierarchies causalexplain.explainability.perm_importance causalexplain.explainability.regression_quality causalexplain.explainability.shapley causalexplain.generators causalexplain.generators.generators causalexplain.generators.mechanisms causalexplain.independence causalexplain.independence.cond_indep causalexplain.independence.edge_orientation causalexplain.independence.effect causalexplain.independence.feature_selection causalexplain.independence.graph_independence causalexplain.independence.hsic causalexplain.independence.kernels causalexplain.independence.mic causalexplain.independence.regressors causalexplain.metrics causalexplain.metrics.compare_graphs causalexplain.metrics.SID causalexplain.models causalexplain.models._base_models causalexplain.models._columnar causalexplain.models._loss causalexplain.models._models causalexplain.models._weight_utils causalexplain.models.dnn causalexplain.models.gbt

moralize() (DAG method)

N

n_jobs (Rex attribute), [1] n_rows (BaseModel attribute) na() (in module causalexplain.estimators.ges.utils) name (Rex attribute), [1] neighbors() (in module causalexplain.estimators.ges.utils) NNRegressor (class in causalexplain.models) (class in causalexplain.models.dnn)

noise() (in module causalexplain.generators.mechanisms) NOTEARS (class in causalexplain.estimators.notears.notears) notears_linear() (in module causalexplain.estimators.notears.linear) notears_standard() (in module causalexplain.estimators.notears.main) (NOTEARS method)

O

on_gpu (ShapEstimator attribute) only_directed() (in module causalexplain.estimators.ges.utils) only_undirected() (in module causalexplain.estimators.ges.utils)

order_edges() (in module causalexplain.estimators.ges.utils) out_degree_iter() (DAG method) override_extras() (BaseModel method)

P

p_value (HSIC property) (HSIC_Values attribute) pa() (in module causalexplain.estimators.ges.utils) pairwise_mic() (in module causalexplain.independence.mic) parallel_jobs (ShapEstimator attribute) parent (ShapDiscrepancy attribute) parent_heteroskedasticity (ShapDiscrepancy attribute) parent_model (ShapDiscrepancy attribute) parent_p_value (ShapDiscrepancy attribute) PC (class in causalexplain.estimators.pc.pc) PDAG (class in causalexplain.estimators.pc.pdag) pdag (PC attribute) pdag_to_cpdag() (in module causalexplain.estimators.ges.utils) pdag_to_dag() (in module causalexplain.estimators.ges.utils) pearsonr() (in module causalexplain.estimators.pc.ci_tests) PermutationImportance (class in causalexplain.explainability.perm_importance) phases (GES attribute), [1] pi (Rex attribute), [1] plot() (GraphDiscovery method), [1] (PermutationImportance method) plot_dendogram_correlations() (in module causalexplain.explainability.hierarchies) plot_feature() (in module causalexplain.models._weight_utils) plot_features() (in module causalexplain.models._weight_utils)

pm_() (in module causalexplain.metrics.SID) Polynomial_Mechanism (class in causalexplain.generators.mechanisms) potential_misoriented_edges() (in module causalexplain.common.utils) power_divergence() (in module causalexplain.estimators.pc.ci_tests) precision (Metrics attribute) predict() (CAM method) (Experiment method) (GBTRegressor method), [1] (GraphIndependence method) (MLP method) (NNRegressor method), [1] (NOTEARS method) (PermutationImportance method) (RegQuality static method) (Rex method), [1] (ShapEstimator method) predict_adaptive_lasso() (in module causalexplain.estimators.lingam.utils) predict_step() (DFF method) (MLP method) prepare_experiment_input() (BaseExperiment method) printout_results() (GraphDiscovery method), [1] prog_bar (ShapEstimator attribute) pruning() (in module causalexplain.estimators.cam.pruning)

R

random_state (GBTRegressor attribute), [1] (Rex attribute), [1] RBF (class in causalexplain.models._loss) rbf_dot() (in module causalexplain.independence.kernels) read_json_file() (in module causalexplain.common.utils) recall (Metrics attribute) reciprocity (ShapEstimator attribute) reduce() (Independencies method)

RegQuality (class in causalexplain.explainability.regression_quality) reset_parameters() (LocallyConnected method) retrieve() (Knowledge method), [1] Rex (class in causalexplain.estimators.rex) (class in causalexplain.estimators.rex.rex) root_causes (Rex attribute), [1] run() (GraphDiscovery method), [1] (in module causalexplain.estimators.notears.main) run_feature_selection() (in module causalexplain.independence.regressors)

S

sachs_main() (in module causalexplain.explainability.shapley) sample() (MDN static method) save() (Experiment method), [1] (GraphDiscovery method), [1] save_experiment() (in module causalexplain.common.utils) scaler (BaseModel attribute) score() (GBTRegressor method), [1] (NNRegressor method), [1] (Rex method), [1] score_by_method() (in module causalexplain.common.plot) score_by_subtype() (in module causalexplain.common.plot) score_valid_delete_operators() (GES method) score_valid_insert_operators() (GES method) score_valid_turn_operators() (GES method) score_valid_turn_operators_dir() (GES method) score_valid_turn_operators_undir() (GES method) scores_by_method() (in module causalexplain.common.plot) see_weights_from_input() (in module causalexplain.models._weight_utils) see_weights_to_hidden() (in module causalexplain.models._weight_utils) select_device() (in module causalexplain.common.utils) select_features() (in module causalexplain.independence.feature_selection) selGam() (in module causalexplain.estimators.cam.selGam) selGamBoost() (in module causalexplain.estimators.cam.selGamBoost) selLasso() (in module causalexplain.estimators.cam.selLasso) selLm() (in module causalexplain.estimators.cam.selLm) semi_directed_paths() (in module causalexplain.estimators.ges.utils) separates() (in module causalexplain.estimators.ges.utils) set_colormap() (in module causalexplain.common.plot) set_fit_request() (Rex method), [1] set_predict_request() (PermutationImportance method) (RegQuality method) (Rex method), [1] (ShapEstimator method) set_random_seed() (in module causalexplain.estimators.notears.utils) set_score_request() (Rex method), [1] setup_plot() (in module causalexplain.common.plot) shap_correlation (ShapDiscrepancy attribute)

shap_discrepancies (ShapEstimator attribute) shap_discrepancies() (in module causalexplain.common.plot) shap_discrepancy (ShapDiscrepancy attribute) shap_gof (ShapDiscrepancy attribute) shap_heteroskedasticity (ShapDiscrepancy attribute) shap_model (ShapDiscrepancy attribute) shap_p_value (ShapDiscrepancy attribute) shap_values() (in module causalexplain.common.plot) ShapDiscrepancy (class in causalexplain.explainability.shapley) ShapEstimator (class in causalexplain.explainability.shapley) shaps (Rex attribute), [1] shd (Metrics attribute) sid (Metrics attribute) SID() (in module causalexplain.metrics.SID) SigmoidAM_Mechanism (class in causalexplain.generators.mechanisms) SigmoidMix_Mechanism (class in causalexplain.generators.mechanisms) silent (ShapEstimator attribute) simulate_dag() (in module causalexplain.estimators.notears.utils) simulate_from_dag_lg() (in module causalexplain.estimators.notears.utils) simulate_linear_sem() (in module causalexplain.estimators.notears.utils) simulate_nonlinear_sem() (in module causalexplain.estimators.notears.utils) simulate_parameter() (in module causalexplain.estimators.notears.utils) skeleton() (in module causalexplain.estimators.ges.utils) skeleton_to_pdag() (PC static method) sort() (in module causalexplain.estimators.ges.utils) stat (HSIC property) (HSIC_Values attribute) state_counts() (StructureEstimator method) state_names (StructureEstimator attribute) step() (LBFGSBScipy method) stringfy_object() (in module causalexplain.common.utils) StructureEstimator (class in causalexplain.estimators.pc.estimators) subplots() (in module causalexplain.common.plot) subsets() (in module causalexplain.estimators.ges.utils) SufficientSets (class in causalexplain.independence.cond_indep) summarize_knowledge() (Rex method), [1] summarize_weights() (in module causalexplain.models._weight_utils)

T

target (ShapDiscrepancy attribute) test() (in module causalexplain.independence.feature_selection) threshold_output() (in module causalexplain.estimators.notears.utils) Tn (Metrics attribute) to_csv() (AcyclicGraphGenerator method) to_daft() (DAG method) to_dag() (PDAG method) to_dict() (Metrics method) to_pdag() (DAG method) topological_ordering() (in module causalexplain.estimators.ges.utils) total_effects_ (BootstrapResult property) Tp (Metrics attribute) TraceExpm (class in causalexplain.estimators.notears.trace_expm) train() (MLPModel method) train_gam() (in module causalexplain.estimators.cam.train_gam)

train_gam_sm() (in module causalexplain.estimators.cam.train_gam) train_GAMboost() (in module causalexplain.estimators.cam.train_GAMboost) train_gp() (in module causalexplain.estimators.cam.train_gp) train_lasso() (in module causalexplain.estimators.cam.train_lasso) train_linear() (in module causalexplain.estimators.cam.train_linear) train_LMboost() (in module causalexplain.estimators.cam.train_LMboost) train_loader (BaseModel attribute) training_step() (DFF method) (MDN method) (MLP method) tune() (GBTRegressor method), [1] (NNRegressor method), [1] tune_fit() (GBTRegressor method), [1] (NNRegressor method), [1] turn() (GES method) turning_step() (GES method)

U

unique_rows() (in module causalexplain.metrics.SID)

updateScoreMat() (in module causalexplain.estimators.cam.updateScoreMat)

V

val_loader (BaseModel attribute) valid_candidates_from_prior() (in module causalexplain.common.utils) valid_output_name() (in module causalexplain.common.utils) validation_step() (DFF method) (MDN method) (MLP method)

values_distribution() (in module causalexplain.common.plot) variables (StructureEstimator attribute) verbose (Rex attribute), [1] (ShapEstimator attribute) vstructures() (in module causalexplain.estimators.ges.utils)

W

weight (LocallyConnected attribute)