DETECTION OF SIMILAR MACHINE LEARNING FEATURES IN REAL-TIME FOR DECLARATIVE FEATURE ENGINEERING

There are provided systems and methods for detection of similar machine learning features in real-time for declarative feature engineering. A service provider, such as an electronic transaction processor for digital transactions, may utilize computing services that implement machine learning models for decision-making of data including real-time data in production computing environments. Machine learning models may utilize features or variables that may correspond to coded logic that provides a measurable datum, property, or the like to the models for intelligent outputs. When creating features, preexisting features may accomplish the same or similar function. Thus, the service provider may provide machine learning clustering of features for similarity detection in real-time. Feature clusters may be precomputed and loaded for comparison using representative vectors for clusters. Each feature may have a declarative definition of parameters that may be used for comparison, and similar detected features may be output during feature engineering.