In order to solve the problem of overfitting caused by combining too many classifiers, a novel maximum fitting-based TrAdaBoost (M-TAB) is proposed to identify ...
This paper constructs the M-TAB method for detecting. P300 potentials across multiple subjects. The method first trains the fusion classifier through a small ...
A novel maximum fitting-based TrAdaBoost (M-TAB) is proposed to identify the P300 potential across multiple subjects to solve the problem of overfitting ...
A Maximum Fitting-based TrAdaBoost Method for Detecting Multiple Subjects' P300 Potentials ... For detection of single-trial, event-related potentials ... two ...
TrAdaBoost is a method that transfers the knowledge from source area to target area, which improves learning effect in the target area. Our research purposed a ...
Missing: Maximum Fitting-
This study proposes a novel training method, TrAdaBoost based on cross-validation and an adaptive threshold (CV-T-TAB), to reduce the amount of data required ...
Missing: Maximum | Show results with:Maximum
A Maximum Fitting-based TrAdaBoost Method for Detecting Multiple Subjects' P300 Potentials · Mengfan Li; Fang Lin; Guizhi Xu. Published on 01 Feb 2020. 0views ...
A TrAdaBoost-based method for detecting multiple subjects' P300 potentials. Individual differences of P300 potentials lead to that a large amount of training ...
A TrAdaBoost Method for Detecting Multiple Subjects' N200 and P300 Potentials Based on Cross-Validation and an Adaptive Threshold · The Study of Generic Model ...
TrAdaBoost is a method that transfers the knowledge from source area to target area, which improves learning effect in the target area. Our research purposed a ...
Missing: Maximum | Show results with:Maximum