Figure 3.

The Scree-plot used for determining the number of principal components. The Scree-plot (the lines above the bar plots) and variance explained by the percentage bar plots, are both used for the number of principal component selection towards PCA for seven normalization techniques. Raw (A) and seven different normalized data (B-H) all applied for PCA. In a result, the variances information of each set of principal components (PC1, PC2, PC3 … and PC13) is extracted from the PCA to show the significance. Either higher variance values of principal components, or prior to bending point “elbow” in the Scree-plot, they both indicate necessary number of principal component usage for the reduced data dimension representation.

Uragun and Rajan BMC Neuroscience 2013 14:114   doi:10.1186/1471-2202-14-114
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