1. A method for generating attribute class statistics for decision tree nodes, comprising: encoding a training dataset in a tabular format, wherein the training dataset comprises a continuous attribute and a discrete attribute, and wherein the continuous attribute and the discrete attribute each have an attribute value; querying the encoded training dataset to extract an attribute class statistics (“ACS”) dataset, wherein the attribute class statistics for the continuous attribute and the discrete attribute are stored in a same format, wherein the format includes a count attribute comprising a list of attribute/class pair counts for the discrete attribute, and wherein the count attribute comprises a number of attribute/class pairs where the attribute value is less than a splitting value for the continuous attribute; and storing the attribute class statistics in a tabular format on a non-transitory computer readable medium.