首页|Study Findings on Machine Learning Described by a Researcher at University of Mi chigan (Comparative Analysis of Machine Learning Models for Music Recommendation )
Study Findings on Machine Learning Described by a Researcher at University of Mi chigan (Comparative Analysis of Machine Learning Models for Music Recommendation )
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators publish new report on ar tificial intelligence. According to news originatingfrom Ann Arbor, Michigan, b y NewsRx editors, the research stated, “Abstract.”Our news correspondents obtained a quote from the research from University of Mi chigan: “This studyis inspired by the Kaggle competition WSDM - KKBoxs Music Re commendation Challenge. The studyfocuses on doing a comparative study on music recommendation models. Based on the requirements andthe given dataset from the Kaggle competition, the problem can be transferred to a classification problem,and therefore, we chose three classification models for the comparative study. T he three models are KNearest Neighbors (KNN), Random Forest, and Light Gradient Boosting Machine (LightGBM).”
University of MichiganAnn ArborMichi ganUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesM achine Learning
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