update error analysis documentation to clarify the error tree splits …

…on errors even when other metrics are selected (#1349)

Co-authored-by: Vinutha Karanth <vinutha.karanth@gmail.com>

libs/localization/src/lib/en.json

@@ -328,8 +328,8 @@
       "defaultLabelCopy": "All data copy"
     },
     "TreeView": {
-      "treeDescription": "The tree visualization uses the mutual information between each feature and the error to best separate error instances from success instances hierarchically in the data. This simplifies the process of discovering and highlighting common failure patterns. To find important failure patterns, look for nodes with a stronger red color (i.e., high error rate) and a higher fill line (i.e., high error coverage). To edit the list of features being used in the tree, click on \"Feature list.\"",
-      "treeStaticDescription": "The tree visualization uses the mutual information between each feature and the error to best separate error instances from success instances hierarchically in the data. This simplifies the process of discovering and highlighting common failure patterns. To find important failure patterns, look for nodes with a stronger red color (i.e., high error rate) and a higher fill line (i.e., high error coverage). To view the list of features used in creating this error tree, click on \"Feature list.\"",
+      "treeDescription": "The tree visualization uses the mutual information between each feature and the error to best separate error instances from success instances hierarchically in the data. This simplifies the process of discovering and highlighting common failure patterns. To find important failure patterns, look for nodes with a stronger red color (i.e., high error rate) and a higher fill line (i.e., high error coverage). To edit the list of features being used in the tree, click on \"Feature list.\" Use the \"select metric\" dropdown menu to learn more about your error and success nodes' performance. Please note that this metric selection will not impact the way your error tree is generated.",
+      "treeStaticDescription": "The tree visualization uses the mutual information between each feature and the error to best separate error instances from success instances hierarchically in the data. This simplifies the process of discovering and highlighting common failure patterns. To find important failure patterns, look for nodes with a stronger red color (i.e., high error rate) and a higher fill line (i.e., high error coverage). To view the list of features used in creating this error tree, click on \"Feature list.\" Use the \"select metric\" dropdown menu to learn more about your error and success nodes' performance. Please note that this metric selection will not impact the way your error tree is generated.",
       "disabledWarning": "Error treemap is disabled unless global cohort is switched to represent \"All data\" due to the treemap being generated for the full dataset. Switch back to the full dataset to view the error treemap."
     },
     "WhatIfPanel": {