1. A machine learning device comprising: a communications interface arranged to receive training data; a tree training logic arranged to train a random decision forest using the received training data and on a basis of uncertainty measures taken at a plurality of split nodes of at least some of the received training data computed using an uncertainty measurement logic; the tree training logic further arranged to train the random decision forest at least on a basis of a bias-corrected Gini index; and the uncertainty measurement logic arranged to calculate a measure of uncertainty which is bias corrected in case of classification tasks or which uses a non-parametric estimate of the uncertainty in case of regression.