索引

A

ape() (在模块 causalml.metrics 中) arr_evaluate_Chi() (causalml.inference.tree.UpliftTreeClassifier 静态方法) arr_evaluate_CIT() (causalml.inference.tree.UpliftTreeClassifier 静态方法) arr_evaluate_CTS() (causalml.inference.tree.UpliftTreeClassifier 静态方法) arr_evaluate_DDP() (causalml.inference.tree.UpliftTreeClassifier 静态方法)

arr_evaluate_ED() (causalml.inference.tree.UpliftTreeClassifier 静态方法) arr_evaluate_IDDP() (causalml.inference.tree.UpliftTreeClassifier 静态方法) arr_evaluate_IT() (causalml.inference.tree.UpliftTreeClassifier 静态方法) arr_evaluate_KL() (causalml.inference.tree.UpliftTreeClassifier 静态方法) arr_normI() (causalml.inference.tree.UpliftTreeClassifier 方法) auuc_score() (在模块 causalml.metrics 中)

B

bar_plot_summary() (在模块 causalml.dataset 中) bar_plot_summary_holdout() (在模块 causalml.dataset 中) BaseDRIVLearner (类在 causalml.inference.iv 中) BaseDRIVRegressor (类在 causalml.inference.iv 中) BaseDRLearner (类在 causalml.inference.meta 中) BaseDRRegressor (类在 causalml.inference.meta 中) BaseRClassifier (类在 causalml.inference.meta 中) BaseRLearner (类在 causalml.inference.meta 中) BaseRRegressor (类在 causalml.inference.meta 中) BaseSClassifier (类在 causalml.inference.meta 中) BaseSLearner (类在 causalml.inference.meta 中)

BaseSRegressor (类在 causalml.inference.meta 中) BaseTClassifier (类在 causalml.inference.meta 中) BaseTLearner (类在 causalml.inference.meta 中) BaseTRegressor (类在 causalml.inference.meta 中) BaseXClassifier (类在 causalml.inference.meta 中) BaseXLearner (类在 causalml.inference.meta 中) BaseXRegressor (类在 causalml.inference.meta 中) bootstrap() (causalml.inference.iv.BaseDRIVLearner 方法) (causalml.inference.tree.CausalTreeRegressor 方法) (causalml.inference.tree.UpliftRandomForestClassifier 静态方法) bootstrap_pool() (causalml.inference.tree.CausalTreeRegressor 方法)

C

calculate_error() (causalml.inference.tree.CausalRandomForestRegressor 方法) calibrate() (在模块 causalml.propensity 中) caliper (causalml.match.NearestNeighborMatch 属性) cat_continuous() (在模块 causalml.inference.tree 中) cat_group() (在模块 causalml.inference.tree 中) cat_transform() (在模块 causalml.inference.tree 中) causalml 模块 causalml.dataset 模块 causalml.feature_selection 模块 causalml.features 模块 causalml.inference.iv 模块 causalml.inference.meta 模块 causalml.inference.tree 模块

causalml.match 模块 causalml.metrics 模块 causalml.optimize 模块 causalml.propensity 模块 CausalRandomForestRegressor (causalml.inference.tree 中的类) causalsens() (causalml.metrics.SensitivitySelectionBias 方法) CausalTreeRegressor (causalml.inference.tree 中的类) check_table_one() (causalml.match.MatchOptimizer 方法) classification_metrics() (在模块 causalml.metrics 中) classify() (causalml.inference.tree.UpliftTreeClassifier 静态方法) compute_propensity_score() (在模块 causalml.propensity 中) CounterfactualUnitSelector (causalml.optimize 中的类) CounterfactualValueEstimator (causalml.optimize 中的类) create_table_one() (在模块 causalml.match 中) cv_fold_index() (在模块 causalml.inference.tree 中)

D

DecisionTree (causalml.inference.tree 中的类) distr_plot_single_sim() (在模块 causalml.dataset 中)

divideSet() (causalml.inference.tree.UpliftTreeClassifier 静态方法) divideSet_len() (causalml.inference.tree.UpliftTreeClassifier 静态方法)

E

ElasticNetPropensityModel (class in causalml.propensity) estimate_ate() (causalml.inference.iv.BaseDRIVLearner method) (causalml.inference.meta.BaseDRLearner method) (causalml.inference.meta.BaseRLearner method) (causalml.inference.meta.BaseSLearner method) (causalml.inference.meta.BaseTLearner method) (causalml.inference.meta.BaseXLearner method) (causalml.inference.meta.LRSRegressor method) (causalml.inference.meta.TMLELearner method) (causalml.inference.tree.CausalTreeRegressor method)

evaluate_Chi() (causalml.inference.tree.UpliftTreeClassifier static method) evaluate_CIT() (causalml.inference.tree.UpliftTreeClassifier static method) evaluate_CTS() (causalml.inference.tree.UpliftTreeClassifier static method) evaluate_DDP() (causalml.inference.tree.UpliftTreeClassifier static method) evaluate_ED() (causalml.inference.tree.UpliftTreeClassifier static method) evaluate_IDDP() (causalml.inference.tree.UpliftTreeClassifier static method) evaluate_IT() (causalml.inference.tree.UpliftTreeClassifier static method) evaluate_KL() (causalml.inference.tree.UpliftTreeClassifier static method)

F

fill() (causalml.inference.tree.UpliftTreeClassifier method) fillTree() (causalml.inference.tree.UpliftTreeClassifier method) filter_D() (causalml.feature_selection.FilterSelect method) filter_F() (causalml.feature_selection.FilterSelect method) filter_LR() (causalml.feature_selection.FilterSelect method) FilterSelect (class in causalml.feature_selection) fit() (causalml.features.LabelEncoder method) (causalml.features.OneHotEncoder method) (causalml.inference.iv.BaseDRIVLearner method) (causalml.inference.iv.IVRegressor method) (causalml.inference.meta.BaseDRLearner method) (causalml.inference.meta.BaseRClassifier method) (causalml.inference.meta.BaseRLearner method) (causalml.inference.meta.BaseSLearner method) (causalml.inference.meta.BaseTLearner method) (causalml.inference.meta.BaseXClassifier method) (causalml.inference.meta.BaseXLearner method) (causalml.inference.meta.XGBRRegressor method) (causalml.inference.tree.CausalRandomForestRegressor method) (causalml.inference.tree.CausalTreeRegressor method) (causalml.inference.tree.UpliftRandomForestClassifier method) (causalml.inference.tree.UpliftTreeClassifier method) (causalml.optimize.CounterfactualUnitSelector method) (causalml.optimize.PolicyLearner method) (causalml.propensity.GradientBoostedPropensityModel method) (causalml.propensity.PropensityModel method)

fit_predict() (causalml.inference.iv.BaseDRIVLearner method) (causalml.inference.meta.BaseDRLearner method) (causalml.inference.meta.BaseRLearner method) (causalml.inference.meta.BaseSLearner method) (causalml.inference.meta.BaseTLearner method) (causalml.inference.meta.BaseXLearner method) (causalml.inference.tree.CausalTreeRegressor method) (causalml.propensity.PropensityModel method) fit_transform() (causalml.features.LabelEncoder method) (causalml.features.OneHotEncoder method)

G

get_actual_value() (在模块 causalml.optimize 中) get_ate_ci() (causalml.metrics.Sensitivity 方法) get_class_object() (causalml.metrics.Sensitivity 静态方法) get_cumgain() (在模块 causalml.metrics 中) get_cumlift() (在模块 causalml.metrics 中) get_importance() (causalml.feature_selection.FilterSelect 方法) (causalml.inference.iv.BaseDRIVLearner 方法) get_pns_bounds() (在模块 causalml.optimize 中) get_prediction() (causalml.metrics.Sensitivity 方法) get_qini() (在模块 causalml.metrics 中) get_shap_values() (causalml.inference.iv.BaseDRIVLearner 方法) get_synthetic_auuc() (在模块 causalml.dataset 中)

get_synthetic_preds() (在模块 causalml.dataset 中) get_synthetic_preds_holdout() (在模块 causalml.dataset 中) get_synthetic_summary() (在模块 causalml.dataset 中) get_synthetic_summary_holdout() (在模块 causalml.dataset 中) get_tmlegain() (在模块 causalml.metrics 中) get_tmleqini() (在模块 causalml.metrics 中) get_treatment_costs() (在模块 causalml.optimize 中) get_tree_leaves_mask() (在模块 causalml.inference.tree 中) get_uplift_best() (在模块 causalml.optimize 中) gini() (在模块 causalml.metrics 中) GradientBoostedPropensityModel (类在 causalml.propensity 中) group_uniqueCounts() (causalml.inference.tree.UpliftTreeClassifier 方法) growDecisionTreeFrom() (causalml.inference.tree.UpliftTreeClassifier 方法)

H

honestApproach() (causalml.inference.tree.UpliftTreeClassifier 方法)

我

IVRegressor (causalml.inference.iv 中的类)

K

kpi_transform() (在模块 causalml.inference.tree 中)

L

label_encoders (causalml.features.LabelEncoder 属性) (causalml.features.OneHotEncoder 属性) label_maxes (causalml.features.LabelEncoder 属性) LabelEncoder (causalml.features 中的类)

load_data() (在模块 causalml.features 中) LogisticRegressionPropensityModel (causalml.propensity 中的类) logloss() (在模块 causalml.metrics 中) LRSRegressor (causalml.inference.meta 中的类)

M

mae() (在模块 causalml.metrics 中) make_uplift_classification() (在模块 causalml.dataset 中) make_uplift_classification_logistic() (在模块 causalml.dataset 中) mape() (在模块 causalml.metrics 中) match() (causalml.match.NearestNeighborMatch 方法) match_and_check() (causalml.match.MatchOptimizer 方法) match_by_group() (causalml.match.NearestNeighborMatch 方法) MatchOptimizer (causalml.match 中的类) min_obs (causalml.features.LabelEncoder 属性) (causalml.features.OneHotEncoder 属性) MLPTRegressor (causalml.inference.meta 中的类)

模块 causalml causalml.dataset causalml.feature_selection causalml.features causalml.inference.iv causalml.inference.meta causalml.inference.tree causalml.match causalml.metrics causalml.optimize causalml.propensity

N

n_jobs (causalml.match.NearestNeighborMatch 属性)

NearestNeighborMatch (causalml.match 中的类) normI() (causalml.inference.tree.UpliftTreeClassifier 方法)

O

OneHotEncoder (causalml.features 中的类)

P

partial_rsqs_confounding() (causalml.metrics.SensitivitySelectionBias static method) plot() (causalml.metrics.SensitivitySelectionBias static method) (in module causalml.metrics) plot_dist_tree_leaves_values() (in module causalml.inference.tree) plot_gain() (in module causalml.metrics) plot_importance() (causalml.inference.iv.BaseDRIVLearner method) plot_lift() (in module causalml.metrics) plot_qini() (in module causalml.metrics) plot_shap_dependence() (causalml.inference.iv.BaseDRIVLearner method) plot_shap_values() (causalml.inference.iv.BaseDRIVLearner method) plot_tmlegain() (in module causalml.metrics) plot_tmleqini() (in module causalml.metrics) PolicyLearner (class in causalml.optimize) predict() (causalml.inference.iv.BaseDRIVLearner method) (causalml.inference.iv.IVRegressor method) (causalml.inference.meta.BaseDRLearner method) (causalml.inference.meta.BaseRClassifier method) (causalml.inference.meta.BaseRLearner method) (causalml.inference.meta.BaseSClassifier method) (causalml.inference.meta.BaseSLearner method) (causalml.inference.meta.BaseTClassifier method) (causalml.inference.meta.BaseTLearner method) (causalml.inference.meta.BaseXClassifier method) (causalml.inference.meta.BaseXLearner method) (causalml.inference.tree.CausalRandomForestRegressor method) (causalml.inference.tree.CausalTreeRegressor method) (causalml.inference.tree.UpliftRandomForestClassifier method) (causalml.inference.tree.UpliftTreeClassifier method) (causalml.optimize.CounterfactualUnitSelector method) (causalml.optimize.PolicyLearner method) (causalml.propensity.GradientBoostedPropensityModel method) (causalml.propensity.PropensityModel method)

predict_best() (causalml.optimize.CounterfactualValueEstimator method) predict_counterfactuals() (causalml.optimize.CounterfactualValueEstimator method) predict_proba() (causalml.optimize.PolicyLearner method) PropensityModel (class in causalml.propensity) prune() (causalml.inference.tree.UpliftTreeClassifier method) pruneTree() (causalml.inference.tree.UpliftTreeClassifier method)

Q

qini_score() (在模块 causalml.metrics 中)

R

r2_score() (在模块 causalml.metrics 中) random_state (causalml.match.NearestNeighborMatch 属性) ratio (causalml.match.NearestNeighborMatch 属性)

regression_metrics() (在模块 causalml.metrics 中) replace (causalml.match.NearestNeighborMatch 属性) rmse() (在模块 causalml.metrics 中) roc_auc_score() (在模块 causalml.metrics 中)

S

scatter_plot_single_sim() (in module causalml.dataset) scatter_plot_summary() (in module causalml.dataset) scatter_plot_summary_holdout() (in module causalml.dataset) search_best_match() (causalml.match.MatchOptimizer method) Sensitivity (class in causalml.metrics) sensitivity_analysis() (causalml.metrics.Sensitivity method) sensitivity_estimate() (causalml.metrics.Sensitivity method) (causalml.metrics.SensitivityPlaceboTreatment method) (causalml.metrics.SensitivityRandomCause method) (causalml.metrics.SensitivityRandomReplace method) (causalml.metrics.SensitivitySubsetData method) SensitivityPlaceboTreatment (class in causalml.metrics) SensitivityRandomCause (class in causalml.metrics) SensitivityRandomReplace (class in causalml.metrics) SensitivitySelectionBias (class in causalml.metrics) SensitivitySubsetData (class in causalml.metrics) set_fit_request() (causalml.inference.tree.CausalRandomForestRegressor method) (causalml.inference.tree.CausalTreeRegressor method)

set_predict_request() (causalml.inference.tree.CausalRandomForestRegressor method) (causalml.inference.tree.CausalTreeRegressor method) set_score_request() (causalml.inference.tree.CausalRandomForestRegressor method) (causalml.inference.tree.CausalTreeRegressor method) shuffle (causalml.match.NearestNeighborMatch attribute) simulate_easy_propensity_difficult_baseline() (in module causalml.dataset) simulate_hidden_confounder() (in module causalml.dataset) simulate_nuisance_and_easy_treatment() (in module causalml.dataset) simulate_randomized_trial() (in module causalml.dataset) simulate_unrelated_treatment_control() (in module causalml.dataset) single_match() (causalml.match.MatchOptimizer method) smape() (in module causalml.metrics) smd() (in module causalml.match) summary() (causalml.metrics.Sensitivity method) (causalml.metrics.SensitivitySelectionBias method) synthetic_data() (in module causalml.dataset)

T

TMLELearner (causalml.inference.meta 中的类) transform() (causalml.features.LabelEncoder 方法) (causalml.features.OneHotEncoder 方法)

treatment_to_control (causalml.match.NearestNeighborMatch 属性) tree_node_summary() (causalml.inference.tree.UpliftTreeClassifier 方法) tree_node_summary_from_counts() (causalml.inference.tree.UpliftTreeClassifier 静态方法) tree_node_summary_to_arr() (causalml.inference.tree.UpliftTreeClassifier 静态方法)

U

uplift_classification_results() (causalml.inference.tree.UpliftTreeClassifier 方法) uplift_tree_plot() (在模块 causalml.inference.tree 中)

uplift_tree_string() (在模块 causalml.inference.tree 中) UpliftRandomForestClassifier (类在 causalml.inference.tree 中) UpliftTreeClassifier (类在 causalml.inference.tree 中)

X

XGBDRIVRegressor (class in causalml.inference.iv) XGBDRRegressor (class in causalml.inference.meta)

XGBRRegressor (class in causalml.inference.meta) XGBTRegressor (class in causalml.inference.meta)