The University of Akron IdeaExchange@UAkron Williams Honors College, Honors Research The Dr. Gary B. and Pamela S. Williams Honors Projects College Spring 2021 Clustering Data to Classify Hearthstone Decks Tim Inzitari
[email protected] Follow this and additional works at: https://ideaexchange.uakron.edu/honors_research_projects Part of the Artificial Intelligence and Robotics Commons, and the Data Science Commons Please take a moment to share how this work helps you through this survey. Your feedback will be important as we plan further development of our repository. Recommended Citation Inzitari, Tim, "Clustering Data to Classify Hearthstone Decks" (2021). Williams Honors College, Honors Research Projects. 1261. https://ideaexchange.uakron.edu/honors_research_projects/1261 This Dissertation/Thesis is brought to you for free and open access by The Dr. Gary B. and Pamela S. Williams Honors College at IdeaExchange@UAkron, the institutional repository of The University of Akron in Akron, Ohio, USA. It has been accepted for inclusion in Williams Honors College, Honors Research Projects by an authorized administrator of IdeaExchange@UAkron. For more information, please contact
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[email protected]. Clustering Data to Classify Hearthstone Decks Tim Inzitari The University of Akron – Williams Honors College April 2, 2021 1 ABSTRACT The esports game of "Hearthstone" is a collectible card game with a competitive format that has every team submit 4 decks of 30 cards each. Using K-Means clustering an adaptable way to group data for classifying can be made that works well in every update of the game. This system will take in a list of decks and cluster them to easily classify large amounts of information in a timely fashion.