Integrating machine learning models in multidimensional applications

Abstract

Systems, methods, and other embodiments associated with integrating a machine learning model into a target application are described. In one embodiment, a method includes parsing a definition file that represents the selected ML model to (1) identify one or more input features defined for the ML model, and (2) identify one or more output predictions that the ML model is configured to generate. The input features and output predictions are mapped to locations within the target application. An executable script is generated and configured to function as a data controller or a data communication interface to obtain the input values from the target application and pass data between the target application and the ML model. In response to obtaining the output predictions, the output predictions are inserted in one or more result locations within the target application.