29641.Fix - Scikit Learn

Fixed the way :class:ensemble.HistGradientBoostingClassifier and ensemble.HistGradientBoostingRegressor compute their bin edges to properly and consistently handle :term:sample_weight. When sample_weights=None is passed to fit and the number of distinct feature values is less than the specified max_bins, the edges are still set to midpoints between consecutive feature values. Otherwise, the bin edges are set to weight-aware quantiles computed using the averaged inverted CDF method. If n_samples is larger than the subsample parameter, the weights are instead used to subsample the data (with replacement) and the bin edges are set using unweighted quantiles of the subsampled data. By :user:Shruti Nath <snath-xoc> and :user:Olivier Grisel <ogrisel>