Abstract: The present invention relates to systems and methods for model scoring and selection. Six or more metrics that are relevant to the model are initially selected, and weights are assigned to each metric. A first subset of the metrics are selected, including metrics for model fit and model error for primary regression. A second subset of metrics including at least two penalty functions are then selected for percentage of incidence. The scores from the primary regression and penalty calculations are aggregated into a final score. Multiple models can be scored and utilized to select a “best” model via an iterative culling of low scoring models and “breeding” of the high scoring models.
Type:
Grant
Filed:
September 30, 2020
Date of Patent:
May 28, 2024
Assignee:
PREVEDERE INC.
Inventors:
Loren Roger Marti, Richard Wagner, Elena Shatilova
Abstract: The invention disclosed is a system for providing an aggregated econometric database with selectable sources of economic data. The econometric database is accessible to a system application that graphically displays econometric data over selected periods, and allows display of external economic data in conjunction with internal company metrics. The system applications further provide for identifying the features of indicators, economic and business forecasting, and providing alerts based on the available econometric data.
Abstract: The invention disclosed is a system for providing an aggregated econometric database with selectable sources of economic data. The econometric database is accessible to a system application that graphically displays econometric data over selected periods, and allows display of external economic data in conjunction with internal company metrics. The system applications further provide for identifying the features of indicators, economic and business forecasting, and providing alerts based on the available econometric data.