Study on Online Learning Behavior Analysis and Performance Prediction Based on Improved Random Forest Algorithm

اسناد مشابه

• An Improved Random Forest Algorithm for Prediction of Protein-Protein Interaction

  سند علمی۲۰۱۵Tung Thanh Pham

  Protein-protein interaction (PPI) is a combining two or more protein because of biochemical events in any living cell. Protein domains are functional and/or structure units in a protein and consequently they are responsible for protein-protein interaction. Many machine-learning a

• An Improved Random Forest Algorithm for Class-Imbalanced Data Classification and its Application in PAD Risk Factors Analysis

  سند علمی۲۰۱۳Dengju Yao, Jing Yang, Xiaojuan Zhan

  The classification problem is one of the important research subjects in the field of machine learning. However, most machine learning algorithms train a classifier based on the assumption that the number of training examples of classes is almost equal. When a classifier was train

• Optimization of Entrepreneurship Education for College Students Based on Improved Random Forest Algorithm

  مقاله‌ی دسترسی آزاد۲۰۲۲Mobile Information Systems['Dongfeng Jia', 'Zheng Hui', '']

  As we all know, the random forest algorithm has advantages of high classification intensity and wide application range. Nevertheless, it still a lot room for improvement. This paper introduces basic idea working principle algorithm, so this proposes some improved algorithms on ba

• An overview of streamflow prediction using random forest algorithm

  مقاله‌ی دسترسی آزاد۲۰۲۲GSC Advanced Research and Reviews['None Muhammad Jibril', 'None Aliyu Bello', 'None Ismail I Aminu', 'None Awaisu Shafiu Ibrahim', 'None Abba Bashir', 'None Salim Idris Malami', 'None Habibu M.A', 'None Mohammed Mukhtar Magaji', '']

  Since the first application of Artificial Intelligence in field hydrology, there has been a great deal interest exploring aspects future enhancements to hydrology. This is evidenced by increasing number relevant publications published. Random forests (RF) are supervised machine l

• High‐resolution snow depth prediction using Random Forest algorithm with topographic parameters: A case study in the Greiner watershed, Nunavut

  مقاله‌ی دسترسی آزاد۲۰۲۲Hydrological Processes['Julien Meloche', 'Alexandre Langlois', 'Nick Rutter', 'Donald McLennan', 'Alain Royer', 'Paul Billecocq', 'Serguei Ponomarenko', '']

  Increased surface temperatures (0.7°C per decade) in the Arctic affects polar ecosystems by reducing extent and duration of annual snow cover. Monitoring these important needs detailed information on cover properties at resolutions (<100 m) that influence ecological habitats perm

• Development of an efficient cement production monitoring system based on the improved random forest algorithm

  مقاله‌ی دسترسی آزاد۲۰۲۲The International Journal of Advanced Manufacturing Technology['Hanane Zermane', 'Abbes Drardja', '']

  Strengthening production plants and process control functions contribute to a global improvement of manufacturing systems because their cross-functional characteristics in the industry. Companies established various innovative operational strategies; there is increasing competiti