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While existing methods mostly offer local, instance-level explanations, the approach leverages strategy clusters—distinct groups of data treated differently by the model—to reveal global model behavior. A system workflow is provided to explore and explain these clusters and to support multiple ways of using strategies to simplify and improve reference models, validated through an insurance acceptance use case.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/strategyatlas-strategy-analysis-for-machine-learning-interpretability/290567/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/strategyatlas-strategy-analysis-for-machine-learning-interpretability/290567.png","ImageObject",300,407,{"name":92,"@type":93},"Liam","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-29","2026-09-17",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",11,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"Why are local, instance-level explanations considered insufficient for interpreting complex ML models?","Question",{"text":113,"@type":114},"Because they do not explain how the model behaves as a whole, strategy clusters are used to understand global behavior instead.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"What does StrategyAtlas use to interpret complex ML models globally?",{"text":118,"@type":114},"It identifies and interprets strategy clusters, which are groups of data instances handled distinctly by the model.",{"name":120,"@type":111,"acceptedAnswer":121},"How was StrategyAtlas validated in practice?",{"text":122,"@type":114},"Through a use case in automatic insurance acceptance, enabling professional data scientists to understand a complex model and improve the production model based on the insights.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},290567,1789642093,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":140,"language":141,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":142,"faqs":143,"seo_title":144,"seo_description":67,"update_tm":130,"read_time":145,"preview_page_count":4},8796095461564,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","StrategyAtlas: Strategy Analysis for Machine Learning Interpretability  \nCitation for published version (APA):  \nCollaris, D. , & van Wijk, J. J. (2023) . StrategyAtlas: Strategy Analysis for Machine Learning Interpretability. IEEE Transactions on Visualization and Computer Graphics, 29(6), 2996-3008.  \n[https://doi.org/10.1109/TVCG.2022.3146806](https://doi.org/10.1109/TVCG.2022.3146806)  \nDocument license:  \nCC BY  \nDOI:  \n10.1109/TVCG.2022.3146806  \nDocument status and date:  \nPublished: 01/06/2023  \nDocument Version:  \nPublisher’s PDF, also known as Version of Record (includes final page, issue and volume numbers)  \nPlease check the document version of this publication:  \n• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.  \n• The final author version and the galley proof are versions of the publication after peer review.  \n• The final published version features the final layout of the paper including the volume, issue and page numbers.  \nLink to publication  \nGeneral rights  \nCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.  \n• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.  \n• You may not further distribute the material or use it for any profit-making activity or commercial gain  \n• You may freely distribute the URL identifying the publication in the public portal.  \nIf the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license above, please follow below link for the End User Agreement:  \n[www.tue.nl/taverne](www.tue.nl/taverne)  \nTake down policy  \nIf you believe that this document breaches copyright please contact us at:  \n[openaccess@tue.nl](openaccess@tue.nl)  \nproviding details and we will investigate your claim.  \nDownload date: 04. Oct. 2023  \nStrategyAtlas: Strategy Analysis for Machine  \nLearning Interpretability  \nDennis Collaris  and Jarke J. van Wijk   \nAbstract—Businesses in high-risk environments have been reluctant to adopt modern machine learning approaches due to their complex and uninterpretable nature. Most current solutions provide local, instance-level explanations, but this is insufficient for understanding the model as a whole. In this work, we show that strategy clusters (i.e., groups of data instances that are treated distinctly by the model) can be used to understand the global behavior of a complex ML model. To support effective exploration and understanding of these clusters, we introduce STRATEGYATLAS, a system designed to analyze and explain model strategies. Furthermore, it supports multiple ways to utilize these strategies for simplifying and improving the reference model. In collaboration with a large insurance company, we present a use case in automatic insurance acceptance, and show how professional data scientists were enabled to understand a complex model and improve the production model based on these insights.  \nIndex Terms—Visual analytics, machine learning, explainable AI  \n~~ ~~ Ç ~~ ~~  \n1 INTRODUCTION  \nWHILE modern machine learning (ML) techniques have  \ngreat potential to solve a wide spectrum of real-world problems, some businesses have been reluctant to adopt this technology. Especially in high-risk environments, such as health care or the insurance sector, predictive performance alone is not sufficient. When critical decisions are made, we need to be able to hold ML models up to scrutiny. Either the mode","cbCaij71GvlDeKdB","https://ap.wps.com/l/cbCaij71GvlDeKdB","pdf",1439133,14,"English","# Abstract\n# 1 Introduction","[{\"question\":\"Why are local, instance-level explanations considered insufficient for interpreting complex ML models?\",\"answer\":\"Because they do not explain how the model behaves as a whole, strategy clusters are used to understand global behavior instead.\"},{\"question\":\"What does StrategyAtlas use to interpret complex ML models globally?\",\"answer\":\"It identifies and interprets strategy clusters, which are groups of data instances handled distinctly by the model.\"},{\"question\":\"How was StrategyAtlas validated in practice?\",\"answer\":\"Through a use case in automatic insurance acceptance, enabling professional data scientists to understand a complex model and improve the production model based on the insights.\"}]","StrategyAtlas - Strategy Analysis for Machine Learning Interpretability | PDF",35]