Abstract: Provided are systems and methods for generating an agnostic data structure that stores debriefing information for a predictive model. In one example, the method may include receiving training data of a predictive program having a model type from among a plurality of different model types, identifying values of generic debriefing information from the training data which is generic among the different model types and values of semantic debriefing information from the training data which is unique to the model type of the received predictive program from among the plurality of different model types, extracting the values of the generic debriefing information and the values of the semantic debriefing information, and storing the values of the generic debriefing information and the semantic debriefing information within an agnostic debriefing data structure.

Abstract: Techniques are described for identifying an input training dataset stored within an underlying data platform; and transmitting instructions to the data platform, the instructions being executable by the data platform to train a predictive model based on the input training dataset by delegating one or more data processing operations to a plurality of nodes across the data platform.

Abstract: Provided are systems and methods for generating an agnostic data structure that stores debriefing information for a predictive model. In one example, the method may include receiving training data of a predictive program having a model type from among a plurality of different model types, identifying values of generic debriefing information from the training data which is generic among the different model types and values of semantic debriefing information from the training data which is unique to the model type of the received predictive program from among the plurality of different model types, extracting the values of the generic debriefing information and the values of the semantic debriefing information, and storing the values of the generic debriefing information and the semantic debriefing information within an agnostic debriefing data structure.

Abstract: Provided are systems and methods for generating specification of a predictive model. In one example, the method may include receiving a predictive model developed via a test environment, generating a specification for the predictive model, the specification comprising a description of the predictive model in a format that is configured to be parsed and integrated into a predictive analytics application, and storing the generated specification in memory.

Abstract: Techniques are described for identifying an input training dataset stored within an underlying data platform; and transmitting instructions to the data platform, the instructions being executable by the data platform to train a predictive model based on the input training dataset by delegating one or more data processing operations to a plurality of nodes across the data platform.