Hidden unit
= Hidden unit
{title2=$z_j=g_j(\sum_iw_{ij}z_i)$}
A <hidden unit> transforms input information before the final output rather than directly representing a supplied target. Nonlinear hidden features can make a classification linearly separable in feature space even when it is not separable in the original input coordinates.