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Enforcement of the principal component analysis - extreme learning machine algorithm by linear discriminant analysis

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Figure

Fig. 1: Comparison of projections of PCA and LDAin a two-class classification problem: The classes arebetter separated by the projection onto the first LDAbasis vector (w) than the projection onto the first PCAeigenvector.
Fig. 2: LDA-PCA-ELM Framework ( Yˆ is the estimated outputs of the model)
Table 1: Main differences of the ELM algorithm with respect the LDA-PCA-ELM algorithm
Table 3: Statistical results using Acc as the variabletest: Mean Acc in the generalization set (Acc), meanranking (RAcc), z-statistic for the Holm post-hoc test,p-value and corrected alpha (α′Holm) for the same test
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