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. 2021 Mar 29;7:e413. doi: 10.7717/peerj-cs.413

Table 2. Parameters and statistics of the best selected architecture for each proposed framework, in order to predict the Bitcoin price, are described.

Statistics represent the average and standard deviation (in brackets), across the k-folds with k = 3, of the MAPE values. Note that (r) stands for SVR with a radial kernel function, (l) stands for SVR with a linear kernel function, and (p) stands for SVR with a polynomial kernel function. The bold entries highlight the framework with the lowest average of the MAPE’s values across the k-folds.

LSTMNN SVR (r) + LSTMNN SVR (l) + LSTMNN SVR (p) + LSTMNN
# epochs 83 330 319 136
# neurons 50 22 99 93
# batchs 40 96 87 98
γ 11.53
d 1
avg (std) 5.79 (1.00) 6.76 (1.56) 2.66 (0.08) 2.7 (0.31)