{"componentChunkName":"component---src-templates-default-template-tsx","path":"/documentation/services/ticketclassifier/classifier/","result":{"data":{"asciidoc":{"id":"8d08166e-0e6a-5328-9b0b-44d69c472ca5","html":"<div id=\"toc\" class=\"toc\">\n<div id=\"toctitle\">Table of Contents</div>\n<ul class=\"sectlevel1\">\n<li><a href=\"#_hiro_desktop_ticket_classifier\">HIRO Desktop Ticket Classifier</a>\n<ul class=\"sectlevel2\">\n<li><a href=\"#_about_the_ticket_classifier\">About the Ticket Classifier</a></li>\n<li><a href=\"#_getting_access_to_the_application\">Getting access to the application</a></li>\n<li><a href=\"#_upload_training_data\">Upload Training Data</a></li>\n<li><a href=\"#_creating_a_new_version_of_an_existing_classifer\">Creating a new version of an existing classifer</a></li>\n<li><a href=\"#_classifier_details\">Classifier Details</a></li>\n</ul>\n</li>\n</ul>\n</div>\n<div class=\"sect1\">\n<h2 id=\"_hiro_desktop_ticket_classifier\">HIRO Desktop Ticket Classifier</h2>\n<div class=\"sectionbody\">\n<div class=\"sect2\">\n<h3 id=\"_about_the_ticket_classifier\">About the Ticket Classifier</h3>\n<div class=\"paragraph\">\n<p>The Ticket Classifier is an application for data scientist that allows the management of classifiers. A classifier takes uncategorized data and predicts a category from any given input String.\nIn order for a classifier to work, they must be trained first, which happens when you upload training data.</p>\n</div>\n</div>\n<div class=\"sect2\">\n<h3 id=\"_getting_access_to_the_application\">Getting access to the application</h3>\n<div class=\"paragraph\">\n<p>In order to access the HIRO Desktop application Ticket Classifier, a user must be assigned to the correct team. If the classifier is enabled for your instance, you will find a team\ncalled haasXXXX_ticket_classifier in id.almato.ai. Your organisation admin will be able to add you to this team.</p>\n</div>\n</div>\n<div class=\"sect2\">\n<h3 id=\"_upload_training_data\">Upload Training Data</h3>\n<div class=\"paragraph\">\n<p>As described in detail in the section below, the csv file must consist of a list of descriptions and categories.\nIf the csv file doesnt match the required format, the the ticket classifier application will notifiy you. If successfull, a new classifier is immediately being trained.\nDepending on the size of the classifier, it may take a few minutes for the training to be complete. Only trained classifiers can be used to predict the category.</p>\n</div>\n<div class=\"paragraph\">\n<p>The name of the trainingdata is used in the Knowledge Item to reference the classifier</p>\n</div>\n<div class=\"listingblock\">\n<div class=\"content\">\n<pre class=\"highlight\"><code> action(capability: \"ClassifierPredict\", classifier_name: \"swedish\", input_string: InputString, timeout: 3000)</code></pre>\n</div>\n</div>\n</div>\n<div class=\"sect2\">\n<h3 id=\"_creating_a_new_version_of_an_existing_classifer\">Creating a new version of an existing classifer</h3>\n<div class=\"paragraph\">\n<p>In case you want to create a new version of an existing classifier (because you want to add more samples to your training data) simply add content to your existing file and and upload it (keep the filename).\nThe new version will automatically be set as the active one.\nActive means that this version will be used by the Knowledge Items that have reference this classifier_name.\nEach classifier can only ever have one active version. However you can choose which version you want to activate by using the toggle button.</p>\n</div>\n<div class=\"imageblock\">\n<div class=\"content\">\n<img src=\"/7.0/images/ticket_classifier/versions.png\" alt=\"versions\">\n</div>\n</div>\n</div>\n<div class=\"sect2\">\n<h3 id=\"_classifier_details\">Classifier Details</h3>\n<div class=\"paragraph\">\n<p>A trained classifier provides you with the following information</p>\n</div>\n<div class=\"imageblock\">\n<div class=\"content\">\n<img src=\"/7.0/images/ticket_classifier/details.png\" alt=\"details\">\n</div>\n</div>\n<div class=\"paragraph\">\n<p>Model Accuracy:</p>\n</div>\n<div class=\"paragraph\">\n<p>Download: Ability to download the training data (as csv)</p>\n</div>\n<div class=\"paragraph\">\n<p>Duration: How long it took to train the model</p>\n</div>\n<div class=\"paragraph\">\n<p>Dropdown for each category from the trainingdata including one entry for all categories</p>\n</div>\n<div class=\"paragraph\">\n<p>Precision: The higher the precision, the less false positives.\nRecall: The higher the recall, the less false negatives.\nF1 Score: F1 Score is a weighed average between precision and recall.</p>\n</div>\n</div>\n</div>\n</div>","document":{"main":"Ticket Classifier Application","title":"Ticket Classifier Application","subtitle":""},"fields":{"toc":true,"location":["documentation","services","ticketclassifier","classifier"]}},"sidebarYaml":{"id":"6d066bdd-c982-5a69-b909-a31e6fc044e0","showIndex":null}},"pageContext":{"id":"8d08166e-0e6a-5328-9b0b-44d69c472ca5","parent":"documentation"}},"staticQueryHashes":["1010459453","1010459453","2356112386","2356112386","2603905930","2603905930","3026652197","3026652197","3167850324","3167850324","63159454","63159454"]}