Predicting the Robustness of Large Real-World Social Networks Using a Machine Learning Model

Table 4

Fit coefficients and the evaluation result given by the MLR. R_IB or R_RD columns show the slope coefficient, and in parenthesis, the standard error values for the NSI. The bold character with an asterisk indicates a significant relationship between the NSI and the robustness R, with a confidence level of 95%.

Nb	NSI	Regression coefficients
		R IB	R RD
1	α	0.113 (0.028)	0.088 (0.026)
2	α^2	−0.118 (0.028)	−0.083 (0.026)
3	α	−0.029 (0.013)	−0.025 (0.012)
4	Q	0.047 (0.02)	0.038 (0.019)
5	C	−0.034 (0.016)	−0.016 (0.015)
6	Cl	0.005 (0.014)	0.007 (0.013)
7	N	−0.013 (0.013)	−0.014 (0.012)
8	<k>	0.077 (0.017)	0.056 (0.016)
9	Intercept	0.173 (0.01)	0.148 (0.009)
MLR results
	RMSE	0.0709	0.0657
	R^2	58.04%	51.76%