Table 4.

Features $u_1-u_{26}$ for the five different feature sets L7–S26. $u_1-u_7$ are linear features, $u_8-u_{14}$ are squared features, $u_{15}-u_{20}$ are cross correlations, and $u_{21}-u_{26}$ are the squared cross correlations.

name → feature ↓	L7	L13	S14	S20	S26
$u_1=m_f$	x	x	x	x	x
$u_2=\mathrm{NVO}$	x	x	x	x	x
$u_3=\mathrm{SOI}$	x	x	x	x	x
$u_4=T_{\mathrm{in}}$	x	x	x	x	x
$u_5=P_{\mathrm{in}}$	x	x	x	x	x
$u_6=\mathrm{IMEP}$	x	x	x	x	x
$u_7=\lambda$	x	x	x	x	x
$u_8=m_f^2$			x	x	x
$u_9=\mathrm{NV}{O}^2$			x	x	x
$u_{10}=\mathrm{SO}{I}^2$			x	x	x
$u_{11}=T_{\mathrm{in}}^2$			x	x	x
$u_{12}=P_{\mathrm{in}}^2$			x	x	x
$u_{13}=\mathrm{IME}{P}^2$			x	x	x
$u_{14}={\lambda }^2$			x	x	x
$u_{15}=m_f\times \mathrm{NVO}$		x		x	x
$u_{16}=m_f\times \mathrm{SOI}$		x		x	x
$u_{17}=\mathrm{NVO}\times \mathrm{SOI}$		x		x	x
$u_{18}=\lambda \times \mathrm{NVO}$		x		x	x
$u_{19}=\lambda \times \mathrm{SOI}$		x		x	x
$u_{20}=\lambda \times m_f$		x		x	x
$u_{21}=(m_f\times \mathrm{NVO}{)}^2$					x
$u_{22}=(m_f\times \mathrm{SOI}{)}^2$					x
$u_{23}=(\mathrm{NVO}\times \mathrm{SOI}{)}^2$					x
$u_{24}=(\lambda \times \mathrm{NVO}{)}^2$					x
$u_{25}=(\lambda \times \mathrm{SOI}{)}^2$					x
$u_{26}=(\lambda \times m_f{)}^2$					x

L stands for linear and S stands for squared.