provided with labeled observations \((x^\ell,y)\), it first fits the logistic regression model \(p_\theta\) of
\(x^\ell\) on \(y\), then labels the unlabelled samples \(x^{u}\) with the observed bad rate in user-defined classes of predicted probabilities of \(p_\theta\) reweighted using user-supplied weights, i.e. \(\hat{y}^{u} = \alpha_k T(k)\) where \(k\) denotes the group (which depends on \(p_\theta\)) and T(k) the observed bad rate of labeled observations in this group.
It then refits a logistic regres