Research Article
Multivariate and Online Prediction of Closing Price Using Kernel Adaptive Filtering
Table 2
Parameter description for close price using ten different KAF algorithms.
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= kernel width, = variance of observation noise, = variance of filter weight diffusion, = step size, = regularization parameter, = Tikhonov regularization, tcoff = learning rate coefficient, = memory size (terms retained in truncation), mu0 = coherence criterion threshold, P = memory length, and nu = approximate linear dependency (ALD) threshold. |