Research project into mining frequent patterns from League of Legends match data. Project composed of data collection, data storage, frequency mining, classification, and analysis. Over 20k matches worth of data was collected from the Riot API via Python and stored in a MongoDB database. Data was then used in mining algorithms in both Python and R. Algorithms used include Apriori, KNN, and Naïve Bayers.
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Research project into mining frequent patterns from League of Legends match data. Project composed of data collection, data storage, frequency mining, classification, and analysis. Over 20k matches worth of data was collected from the Riot API via Python and stored in a MongoDB database.