1. A method of machine-learning classification, comprising: (a) obtaining an item having values for a plurality of different features in a feature set; (b) obtaining scores for the different features, the score for a given feature being a measure of prediction ability for the given feature and having been calculated as a function of a plurality of different occurrence metrics pertaining to the given feature; (c) scaling the values for the features according to the scores for said features, thereby obtaining adjusted feature set values for the item; and (d) classifying the item by inputting the adjusted feature set values for the item into a previously trained classifier.