Patent EP-4209843-A2 (EP)
Title: Method and apparatus for determining stability of an ensemble model of a plurality of forecast models.
Inventor: JELONEK PIOTR ZBIGNIEW
IPC: G05B13/04
Filed: 2023-01-11
Abstract: There is described an apparatus, preferably a robot, for defining and populating a memory storage and preferably outputting an alert and/or outputting an image. The improved data structure of the storage as defined by the robot restructures and streamlines the process by which outputs of the robot can be determined and output. The robot comprises: a user interface and/or a communication interface for receiving a target data series comprising a plurality of observations and/or one or more explanatory data series and/or a plurality of forecast models; a memory storage for storing a data structure for storing intermediate data; a processor for: receiving or determining a plurality of forecast models, each forecast model associated with one or more explanatory data series; defining a data structure in the memory storage in dependence on the number of forecast models and the number of observations of the target data series; performing a leave-one-out process for each forecast model of the plurality of forecast models, wherein the processor determines a predicted value by dropping an observation from the target data series and predicting the dropped observation in dependence on the forecast model and the data of the remaining observations in the target data series; repeating the leave-one-out process for each observation from the target data series to obtain a set of predicted values for each forecast model, wherein the set comprises a number of predicted values less than or equal to the number of observations of the target data series; determining errors between each of the predicted values and the values of the observations; and outputting the predicted values and their associated errors to the data structure in the memory storage; wherein the processor and/or a further processor is configured for: retrieving the intermediate data from the memory storage; receiving or determining an ensemble model, wherein the ensemble model comprises a weighted combination of forecast models, the weighting of each forecast model in the ensemble model being dependent on the respective determined errors; determining a stability measure of the ensemble model by: weighting each of the predicted values for each observation by multiplying the predicted values retrieved from the memory storage by the weighting, wherein the weighting is dependent on the associated determined errors retrieved from the memory storage; determining weighted predicted averages for each observation of the target data series by summing the weighted predicted values over all the models for each observation; and determining errors between observations of the target data series and the weighted predicted averages, such averages having been computed using the processor and/or further processor from the intermediate data stored in the memory storage; , whereby, preferably, the retrieval and computation of the intermediate data from the storage memory can bypass any need for performing full regression analysis on the ensemble model to determine the stability measure, thereby preferably reducing the computational complexity by a factor proportional to the number of observations of the target data series; and outputting the stability measure of the ensemble model, preferably to the user interface and/or communication interface.