   <h2>Details</h2>
    <p>We define the population variable importance measure (VIM) for the
group of features (or single feature) \(s\) with respect to the
predictiveness measure \(V\) by
$$\psi_{0,s} := V(f_0, P_0) - V(f_{0,s}, P_0),$$ where \(f_0\) is
the population predictiveness maximizing function, \(f_{0,s}\) is the
population predictiveness maximizing function that is only allowed to access
the features with index not in \(s\), and \(P_0\) is the true
data-generating distribution. VIM estimates are