Abstract: The current document is directed to methods and systems for estimating values that could be derived from a large data set, were it available, from values computed from an available smaller data set. A specific example of the currently described methods and systems are methods and systems that estimate various medical-record-related statistics and values computed from hypothetical datasets. In order to extrapolate the desired statistics and computed values from the observed smaller data set, multiple models are employed by the currently disclosed methods and systems. These models can be employed sequentially to generate relatively fine-grained estimates over various multi-dimensional data-set volumes.

Abstract: The present document is directed to an automated experimentation platform that provides a visual integrated development environment (“IDE”) that allows a user to construct and execute various types of data-driven workflows. The automated experimentation platform includes back-end components that include API servers, a catalog, a cluster-management component, and execution-cluster nodes. Workflows are visually represents as directed acyclic graphs and texturally encoded. The workflows are transformed into jobs that are distributed for execution to the execution-cluster nodes.