Table 1.

Feature selection through singular vectors (SVs) in data 2

	1st SV (η (1))	2nd SV (η (2))	3rd SV (η (3))
η 1	0.98 (0.002)	0.00 (0.018)	0.00 (0.001)
η 2	0.00 (0.003)	0.21 (0.033)	0.00 (0.001)
η 3	0.00 (0.001)	0.00 (0.010)	0.22 (0.029)
η 4	0.22 (0.013)	0.00 (0.017)	0.00 (0.005)
η 5	0.00 (0.000)	0.98 (0.004)	0.00 (0.005)
η 6	0.00 (0.004)	0.00 (0.002)	0.98 (0.003)
	1st SV (μ (1))	2nd SV (μ (2))	3rd SV (μ (3))
μ 1	0.99 (0.005)	0.01 (0.022)	0.01 (0.014)
μ 2	0.01 (0.027)	0.99 (0.004)	0.01 (0.015)
μ 3	0.01 (0.024)	0.01 (0.018)	0.99 (0.003)
μ 4	0.01 (0.023)	0.01 (0.026)	0.01 (0.017)

These results show mean weight coefficients (standard deviation) in 100 simulation runs. Significant weight coefficients are bold faced