{"id":1525,"date":"2021-05-27T09:05:17","date_gmt":"2021-05-27T16:05:17","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/?post_type=example&#038;p=1525"},"modified":"2023-05-26T05:18:43","modified_gmt":"2023-05-26T12:18:43","slug":"interpretml-g11-b-global-explanations","status":"publish","type":"example","link":"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/example\/interpretml-g11-b-global-explanations\/","title":{"rendered":"InterpretML | 11B: Global explanations"},"content":{"rendered":"<div class=\"toolkit-heading-with-image-block\">\n\t\n\n<h2 class=\"wp-block-heading\">InterpretML | 11B: Global explanations<\/h2>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" src=\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/uploads\/prod\/2023\/05\/yellow-header-bar-1536x14-5-23.png\" alt=\"\" \/><\/figure>\n\n<\/div>\n\n\n\n\n\n<figure class=\"wp-block-image size-large is-style-example\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"806\" src=\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/uploads\/prod\/2021\/05\/18709-G11-B_Global-Explanations_InterpretML-Microsoft_Breast-Cancer-Recurrence-Prediction-One-Feature-annotated.png\" alt=\"Interpret ML gives global explanation.\" class=\"wp-image-1334\" srcset=\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/uploads\/prod\/2021\/05\/18709-G11-B_Global-Explanations_InterpretML-Microsoft_Breast-Cancer-Recurrence-Prediction-One-Feature-annotated.png 1024w, https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/uploads\/prod\/2021\/05\/18709-G11-B_Global-Explanations_InterpretML-Microsoft_Breast-Cancer-Recurrence-Prediction-One-Feature-annotated-300x236.png 300w, https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/uploads\/prod\/2021\/05\/18709-G11-B_Global-Explanations_InterpretML-Microsoft_Breast-Cancer-Recurrence-Prediction-One-Feature-annotated-768x605.png 768w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">This is a model for predicting recurrence of breast cancer based on patient and tumor attributes. InterpretML explains the predictions \u00a0(<a href=\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/guideline\/make-clear-why-the-system-did-what-it-did\/\">Guideline 11<\/a>) by providing information about how a particular feature impacts it (<a href=\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/pattern\/g11-b-global-explanations\/\">Pattern 11B<\/a>). In this example, we see how the tumor size impacts the score (in blue bars) for recurrent events (above zero). For example, tumor sizes lower than 19 are associated with negative scores, meaning no recurrent events. <em><sup><sub>Image captured July 2020.<\/sub><\/sup><\/em><\/figcaption><\/figure>\n","protected":false},"featured_media":1334,"menu_order":0,"template":"","meta":{"toolkit_pattern_number":"11B","ep_exclude_from_search":false,"footnotes":""},"application-type":[69],"goal":[114,126,123],"guideline-term":[13],"product-category":[62],"class_list":["post-1525","example","type-example","status-publish","has-post-thumbnail","hentry","application-type-prediction","goal-appropriate-reliance","goal-reliability","goal-transparency","guideline-term-make-clear-why-the-system-did-what-it-did","product-category-health-and-wellness"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v23.7 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>InterpretML | 11B: Global explanations - Microsoft HAX Toolkit<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/example\/interpretml-g11-b-global-explanations\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"InterpretML | 11B: Global explanations - Microsoft HAX Toolkit\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/example\/interpretml-g11-b-global-explanations\/\" \/>\n<meta property=\"og:site_name\" content=\"Microsoft HAX Toolkit\" \/>\n<meta property=\"article:modified_time\" content=\"2023-05-26T12:18:43+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/uploads\/prod\/2021\/05\/18709-G11-B_Global-Explanations_InterpretML-Microsoft_Breast-Cancer-Recurrence-Prediction-One-Feature-annotated.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1024\" \/>\n\t<meta property=\"og:image:height\" content=\"806\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 minute\" \/>\n\t<meta name=\"twitter:label2\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data2\" content=\"Shipi Dhanorkar\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/example\/interpretml-g11-b-global-explanations\/\",\"url\":\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/example\/interpretml-g11-b-global-explanations\/\",\"name\":\"InterpretML | 11B: Global explanations - Microsoft HAX Toolkit\",\"isPartOf\":{\"@id\":\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/example\/interpretml-g11-b-global-explanations\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/example\/interpretml-g11-b-global-explanations\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/uploads\/prod\/2021\/05\/18709-G11-B_Global-Explanations_InterpretML-Microsoft_Breast-Cancer-Recurrence-Prediction-One-Feature-annotated.png\",\"datePublished\":\"2021-05-27T16:05:17+00:00\",\"dateModified\":\"2023-05-26T12:18:43+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/example\/interpretml-g11-b-global-explanations\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/example\/interpretml-g11-b-global-explanations\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/example\/interpretml-g11-b-global-explanations\/#primaryimage\",\"url\":\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/uploads\/prod\/2021\/05\/18709-G11-B_Global-Explanations_InterpretML-Microsoft_Breast-Cancer-Recurrence-Prediction-One-Feature-annotated.png\",\"contentUrl\":\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/uploads\/prod\/2021\/05\/18709-G11-B_Global-Explanations_InterpretML-Microsoft_Breast-Cancer-Recurrence-Prediction-One-Feature-annotated.png\",\"width\":1024,\"height\":806,\"caption\":\"This is a model for predicting recurrence of breast cancer based on patient and tumor attributes. 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