Mathematical Problems in Engineering / 2020 / Article / Tab 3

Research Article

Sparse Principal Component Analysis via Fractional Function Regularity

Table 3

Loadings and variance of numerical results of PCA, SPCA, and FP-SPCA methods in Case 2, where the FP-SPCA method works better than SPCA in obtaining the sparse loadings. (%) denotes the adjusted variance.

PCASPCAFP-SPCA
PC1PC2PC3PC1PC2PC1PC2

−0.3472−0.35030.0819−0.3565−0.3466−0.50
−0.3472−0.35030.0819−0.3565−0.3466−0.50
−0.3472−0.35030.0819−0.3565−0.3466−0.50
−0.3472−0.35030.0819−0.3565−0.3466−0.50
−0.34440.35660.0651−0.35050.360400.5
−0.34440.35660.0651−0.35050.360400.5
−0.34440.35660.0651−0.35050.360400.5
−0.34440.35660.0651−0.35050.360400.5
−0.1472−0.0159−0.69140000
−0.1472−0.0159−0.69140000
(%)49.2332.1018.6744.6129.8840.0038.44

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