Semi-Supervised Ensemble Learning // Weighted-ensemble regression over base learners supported by 'caret' (Kuhn (2008) doi:10.18637/jss.v028.i05), with cross-validated hyperparameter selection, out-of-fold diagnostics, and signed residual- offset estimates. Multi-response problems use iterative input-space expansion related to Spyromitros-Xioufis et al. (2016) doi:10.1007/s10994-016-5546-z, with Jacobi or 'Gauss-Seidel' sweeps, package-defined companion gates and per-response iteration stitching. A package-defined pseudo-label stage promotes prediction rows by a cross-model and cross-dataset range ratio and accepts rounds with an out-of-fold squared- correlation gauge.