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docs/examples/Multiple_Models_Interface_With_Error_Analysis.ipynb

@@ -208,7 +208,7 @@
     "\n",
     "* **n_estimators**: int, the number of estimators for bootstrap to compute subgroup stability metrics.\n",
     "\n",
-    "* **computation_mode**: str, 'default' or 'error_analysis'. Name of the computation mode. When a default computation mode measures metrics for sex_priv and sex_dis, an `error_analysis` mode measures metrics for (sex_priv, sex_priv_correct, sex_priv_incorrect) and (sex_dis, sex_dis_correct, sex_dis_incorrect). Therefore, a user can analyze how a model is certain about its incorrect predictions.\n",
+    "* **computation_mode**: str, 'default', 'error_analysis', or 'no_bootstrap'. Name of the computation mode. When a default computation mode measures metrics for sex_priv and sex_dis, an `error_analysis` mode measures metrics for (sex_priv, sex_priv_correct, sex_priv_incorrect) and (sex_dis, sex_dis_correct, sex_dis_incorrect). Therefore, a user can analyze how a model is certain about its incorrect predictions.\n",
     "\n",
     "* **sensitive_attributes_dct**: dict, a dictionary where keys are sensitive attribute names (including intersectional attributes), and values are disadvantaged values for these attributes. Intersectional attributes must include '&' between sensitive attributes. You do not need to specify disadvantaged values for intersectional groups since they will be derived from disadvantaged values in sensitive_attributes_dct for each separate sensitive attribute in this intersectional pair.\n",
     "\n",