Abstract: A system, method, and computer program product provides a multi-category apply operation in a data mining system that produces output with multiple class values, their associated measures including probabilities in case of supervised models, quality of fit and distance in case of clustering models, and the relative ranks of the predictions. A method for multi-category apply in a data mining system comprises the steps of receiving input data for scoring including a plurality of rows of data applied to a data mining model and generating multi-category apply output including a plurality of class values and their associated probabilities based on the received input data, the selected class values having probabilities meeting a selection criterion and their ranks.

Abstract: A system, method, and computer program product provides a multi-category apply operation in a data mining system that produces output with multiple class values, their associated measures including probabilities in case of supervised models, quality of fit and distance in case of clustering models, and the relative ranks of the predictions. A method for multi-category apply in a data mining system comprises the steps of receiving input data for scoring including a plurality of rows of data applied to a data mining model and generating multi-category apply output including a plurality of class values and their associated probabilities based on the received input data, the selected class values having probabilities meeting a selection criterion and their ranks.