首页|Data from Universitas Muhammadiyah Malang Provide New Insights into Boltzmann Ma chines (The Implementation of Restricted Boltzmann Machine in Choosing a Special ization for Informatics Students)
Data from Universitas Muhammadiyah Malang Provide New Insights into Boltzmann Ma chines (The Implementation of Restricted Boltzmann Machine in Choosing a Special ization for Informatics Students)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Boltzmann machines are p resented in a new report. According to news reporting out of the Universitas Muh ammadiyah Malang by NewsRx editors, research stated, “Choosing a specialization was not an easy task for some students, especially for those who lacked confiden ce in their skill and ability.” Our news journalists obtained a quote from the research from Universitas Muhamma diyah Malang: “Specialization in tertiary education became the benchmark and key to success for students’ future careers. This study was conducted to provide th e learning outcomes record, which showed the specialization classification for t he Informatics students by using the data from the students of 2013-2015 who had graduated. The total data was 319 students. The classification method used for this study was the Restricted Boltzmann Machine (RBM). However, the data showed imbalanced class distribution because the number of each field differed greatly. Therefore, SMOTE was added to classify the imbalanced class.” According to the news reporters, the research concluded: “The accuracy obtained from the combination of RBM and SMOTE was 70% with a 0.4 mean squa red error.”
Universitas Muhammadiyah MalangBoltzma nn MachineEmerging TechnologiesMachine Learning
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