19. A computer program product for multi-category apply in a data mining system comprising: a computer readable medium encoded with computer program instructions, recorded on the computer readable medium, executable by a processor, for performing the steps of receiving scoring data including scores of rows of data representing real-world quantities applied to a data mining model, including distance, wherein the scoring data is received in a transactional format and is prepared to generate input data tables including active attributes and source attributes; and selecting a plurality of categories, each category representing a discrete value or a set of values of a class by generating multi-category apply data, the multi-category apply data generated by: generating input data tables including active attributes and source attributes; evaluating measures including probabilities and ranks of categories of a target attribute to determine those meeting a selection criterion for supervised models; and evaluating measures including probabilities, ranks, quality of fit, and distance of predicted values to determine those meeting the selection criterion for unsupervised models; and generating an output data table including a plurality of class values of the target attribute meeting the selection criterion and their associated measures including probabilities, ranks, quality of fit and distance based on the received scoring data.
19. A computer program product for multi-category apply in a data mining system comprising: a computer readable medium encoded with computer program instructions, recorded on the computer readable medium, executable by a processor, for performing the steps of receiving scoring data including scores of rows of data representing real-world quantities applied to a data mining model, including distance, wherein the scoring data is received in a transactional format and is prepared to generate input data tables including active attributes and source attributes; and selecting a plurality of categories, each category representing a discrete value or a set of values of a class by generating multi-category apply data, the multi-category apply data generated by: generating input data tables including active attributes and source attributes; evaluating measures including probabilities and ranks of categories of a target attribute to determine those meeting a selection criterion for supervised models; and evaluating measures including probabilities, ranks, quality of fit, and distance of predicted values to determine those meeting the selection criterion for unsupervised models; and generating an output data table including a plurality of class values of the target attribute meeting the selection criterion and their associated measures including probabilities, ranks, quality of fit and distance based on the received scoring data. 20. The computer program product of claim 19 , further comprising the step of: validating the received scoring data to ensure active attributes and a target attribute specified for the data mining model are present in the received scoring data and the source attributes specified for the multi-category apply output are present in the input data.