Sas Institute Inc.

Robert Wayne Thompson

Xiangqian Hu

Xiangxiang Meng

Peter Rowland Eastwood

Adam Michael Ames

Rajendra Prasad Singh

Thomas Francis Mutdosch

Ryan Gillespie

Yue Qi

Rory David Ness MacKenzie

Andrew John Knotts

Jeffrey Todd Miller, Jr

Iain Douglas Jackson

Duane Hamilton

A system can obtain observations from a dataset. The system can generate a set of training partitions based on the observations and generate an ensemble of machine-learning models based on the set of training partitions. The system can then receive new data and detect whether the new data is indicative of the event using the ensemble. In some cases, the system can update the ensemble by providing the new data as input to an unsupervised machine-learning model that is separate from the ensemble of machine-learning models; receiving an output from the unsupervised machine-learning model indicating whether or not the new data is indicative of the event; incorporating a new observation into the dataset indicating whether or not the new data is indicative of the event based on the output from the unsupervised machine-learning model; and updating the ensemble based on the dataset with the new observation.

Advanced detection of rare events and corresponding interactive graphical user interface

Techniques for providing interactive decision trees are included. For example, a system is provided that stores data related to a decision tree, wherein the data includes one or more data structures and one or more portions of code. The system receives input corresponding to an interaction request associated with a modification to the decision tree. The system determines whether the modification requires multiple-processing iterations of the distributed data set. The system generates an application layer modified decision tree when the generating requires no multiple-processing iterations of the distributed data set. The system facilitates server layer modification of the decision tree when the modification requires multiple-processing iterations of the distributed data set. The system generates a representation of the application layer modified decision tree or the server layer modified decision tree.

Techniques for interactive decision trees

Growing community of inventors

Cary, NC, United States of America

Robert Wayne Thompson