1. A method for machine learning a data set in a data processing framework, comprising: generating a forest comprising a plurality of trees that each include a plurality of leaf nodes, said generating based on initial training data that includes the data set, said generating including: generating the plurality of trees in parallel, and assigning a constant weight to each leaf node of the plurality of leaf nodes; constructing new training data based on the generated forest and the initial training data; determining a discriminative value for each of the plurality of leaf nodes in parallel based on the new training data to determine a plurality of discriminative values; and reconstructing the forest with the discriminative values replacing the constant weight for each of the plurality of leaf nodes.