Revert "Update ur_config.md"

This reverts commit 7022838.

Author: zebraf1

ur_config.md

@@ -139,7 +139,7 @@ A full list of tuning and config parameters is below. See the field description
                 "minLLR": 5
             }
         ],
-        "blacklistIndicators": ["buy", "view"],
+        "blacklistEvents": ["buy", "view"],
         "maxEventsPerEventType": 500,
         "maxCorrelatorsPerEventType": 50,
         "maxQueryEvents": 100,
@@ -219,7 +219,7 @@ The `Algorithm: params:` section controls most of the features of the UR. Possib
   * **minLLR**: this is not used by default and is here when an LLR score is desired as the minimum threshold. Since LLR scores will be higher for better correlation this can be set to ensure the highest quality correlators are the only ones used. This will increase precision of recommendations but may decrease recall, meaning you will get better recommendations but less of them. Increasing this may affect results negatively so always A/B test any tweaking of this value. There is no default, we keep `maxCorrelatorsPerItem` of the highest scores by defaultf—no matter the score. A rule of thumb would say to use something like 5 for a typical high quality ecom dataset.
 * **maxQueryEvents**: optional (use with great care), default = 100. An integer specifying the number of most recent user history events used to make recommendations for an individual. More implies some will be less recent actions. Theoretically using the right number will capture the user’s current interests.
 * **num**: optional, default = 20. An integer telling the engine the maximum number of recommendations to return per query but less may be returned if the query produces less results or post recommendations filters like blacklists remove some.
-* **blacklistIndicators**: optional, default = the primary action. An array of strings corresponding to the actions taken on items, which will cause them to be removed from recommendations. These will have the same values as some user actions - so “purchase” might be best for an ecom application since there is often little need to recommend something the user has already bought. If this is not specified then the primary event is assumed. To blacklist no indicators, specify an empty array. Note that not all actions are taken on the same items being recommended. For instance every time a user goes to a category page this could be recorded as a category preference so if this event is used in a blacklist it will have no effect, the category and item ids should never match. If you want to filter certain categories, use a field filter and specify all categories allowed.
+* **blacklistEvents**: optional, default = the primary action. An array of strings corresponding to the actions taken on items, which will cause them to be removed from recommendations. These will have the same values as some user actions - so “purchase” might be best for an ecom application since there is often little need to recommend something the user has already bought. If this is not specified then the primary event is assumed. To blacklist no event, specify an empty array. Note that not all actions are taken on the same items being recommended. For instance every time a user goes to a category page this could be recorded as a category preference so if this event is used in a blacklist it will have no effect, the category and item ids should never match. If you want to filter certain categories, use a field filter and specify all categories allowed.
 * **fields**: optional, default = none. An array of default field based query boosts and filters applied to every query. The name = type or field name for metadata stored in the EventStore with $set and $unset events. Values = and array of one or more values to use in any query. The values will be looked for in the field name. Bias will either boost the importance of this part of the query or use it as a filter. Positive biases are boosts any negative number will filter out any results that do not contain the values in the field name.
 * **userBias**: optional (use with great care), default = none. Amount to favor user history in creating recommendations, 1 is neutral, and negative number means to use as a filter so the user history must be used in recommendations, any positive number greater than one will boost the importance of user history in recommendations.
 * **itemBias**: optional (use with great care), default = none. Same as userbias but applied to similar items to the item supplied in the query.