Multi-learner based recursive supervised training

• Main Authors: IYER, Laxmi R., RAMANATHAN, Kiruthika, GUAN, Sheng-Uei
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2006
• Subjects: Neural Networks; Supervised Learning; Probabilistic Neural Networks (PNN); Backpropagation; Artificial Intelligence and Robotics; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/9314; https://ink.library.smu.edu.sg/context/sis_research/article/10314/viewcontent/Multi_Learner_based_Recursive_Supervised_Training_av.pdf
• Institution: Singapore Management University

In this paper, we propose the multi-learner based recursive supervised training (MLRT) algorithm, which uses the existing framework of recursive task decomposition, by training the entire dataset, picking out the best learnt patterns, and then repeating the process with the remaining patterns. Inste...