a prediction classifier is trained using historical records from a servicely table and then returns predictions ( classification fields ) for input text ( search fields ) a classifier will have one of more classifier contexts which control the behaviour of the classifier in different contexts (eg via ui, email or virtual agent) each classifier is triggered by a client script defining a classifier perform the following steps to create or modify a prediction classifier navigate to intelligent automation → intelligent predictions → classifiers and select new configure the following fields mandatory fields that must be configured name unique name of classifier table which table will the classifier be applied type for prediction classifiers the type will be "classification" search fields the text field used to trigger classifier classification fields the fields on the form / table that will be predicted by the classifier the table below provides a list of all of the parameters on a classifier record field description notes name unique name of the classifier eg incident table table the classifier reads data from eg incident status status values of the classifier read only field primarily to indicate the status of training type classifiers are used for intelligent prediction, search and response for prediction classifiers, set type classification description description of the classifier search fields the text field used to trigger classifier note normally on single fields selected classification fields the fields on the form / table that will be predicted by the classifier eg category, subcategory and assignment group training start the date / time that the classifier most recent training started training end the date / time that the classifier most recent training started advanced configuration the following section details some of the advanced configuration options for a classifier classifier filters classifier filters allow you to define criteria for improving the relevancy of the classifier results a classifier filter uses information on the current record, such as location, to restrict the training data taken into account by the classifier field description notes filter field classifier uses these fields on the record to filter the results for example, assignment groups for each state (e g qld operations) the filter field can be set to 'assignment group location state' the classifier returns then these records and can filter out assignment groups from other states filter source fields classifier uses the filter source fields to identify the data source used by the filter field for example classifier depends on the state (location) of the caller the filter source field identifies where the state field is defined in this case the state field is located on the user's profile ==> location ==> state (caller location state) modifying classifier results layout field description notes layout provide the option to override the default layout of our classifier prediction results are presented in the sofi service agent assistant intelligent prediction ui sidebar by default this field is blank and sofi uses a default ui layout for prediction classifier results generate default template a ui action at the bottom of the classifier form that generates a layout for the configured classification fields you can use this field to modify the layout for the sofi service agent assistant intelligent prediction ui sidebar an example of the layout syntax is shown below layout \<label>classification \</label> \<section> \<field l2>{{ fields category display }}\</field l2> \<field l2>{{ fields subcategory display }}\</field l2> \</section> \<label>assignment \</label> \<section> \<field>{{ fields assignment group display }}\</field> \</section> 544 other fields field description notes data analytic fields used to collect additional information for data analysis internal use only, please leave blank request parameters internal use only, please leave blank result processor internal use only, please leave blank training a prediction classifer before sofi can be used we need train the models, this is done by navigating to the servicely menu intelligent automation → intelligent predictions → classifiers select the classifier and then click on the train classifier link at the bottom of the form the duration depends on a number of factors and can take between 20 minutes and a few hours the classifier provides a status field indicating the current state allowing you to confirm when training is complete once completed, the training end field will be populated note that during training, the classifier will still make predictions however the results may be inconsistent estimated training duration as a guide, 100,000 may take 20 mins 500,000 may take 2 hours 1,000,000 records may take 4 5 hours