US 2025/0053618 A1 · NODE AND METHODS PERFORMED THEREBY FOR HANDLING DRIFT IN DATA

Abstract

A method performed by a node for handling drift in data. The node obtains a dataset including a plurality of datapoints corresponding to a plurality of values of one or more dependent variables for a plurality of first features over a time period. The node determines, using machine learning and explainability, in the absence of determining whether or not the plurality of datapoints has a drift, whether or not there has been a change in respective one or more characteristics of a subset of the plurality of first features having a largest contribution to a variability of the datapoints in the plurality of datapoints based on a threshold from a first time period to a second time period. The node then initiates application of a drift policy on the plurality of datapoints based on a result of the determination.

Claims21

Dependent claims

A computer-implemented method, performed by a node, the method being for handling drift in data, the node operating in a communications system, the method comprising:

obtaining a dataset comprising a plurality of datapoints corresponding to a plurality of values of one or more dependent variables for a plurality of first features over a time period;
determining, using machine learning and explainability, in the absence of determining whether or not the plurality of datapoints has a drift, whether or not there has been a change in respective one or more characteristics of a subset of the plurality of first features in the plurality of datapoints having a largest contribution to a variability of the datapoints in the plurality of datapoints based on a threshold from a first time period to a second time period;
and
initiating application of a drift policy on the plurality of datapoints based on a result of the determination of whether or not there has been a change.

1 more element

A computer-readable storage medium, having stored thereon a computer program, comprising instructions which, when executed on at least one processor, cause the at least one processor to carry out operations comprising:

obtain a dataset comprising a plurality of datapoints corresponding to a plurality of values of one or more dependent variables for a plurality of first features over a time period;
determine, using machine learning and explainability, in the absence of determining whether or not the plurality of datapoints has a drift, whether or not there has been a change in respective one or more characteristics of a subset of the plurality of first features in the plurality of datapoints having a largest contribution to a variability of the datapoints in the plurality of datapoints based on a threshold from a first time period to a second time period;
and
initiate application of a drift policy on the plurality of datapoints based on a result of the determination of whether or not there has been a change.

1 more element

A node, for handling drift in data, the node being configured to operate in a communications system, the node being further configured to:

obtain a dataset configured to comprise a plurality of datapoints configured to correspond to a plurality of values of one or more dependent variables for a plurality of first features over a time period;
determine, using machine learning and explainability, in the absence of determining whether or not the plurality of datapoints has a drift, whether or not there has been a change in respective one or more characteristics of a subset of the plurality of first features in the plurality of datapoints configured to have a largest contribution to a variability of the datapoints in the plurality of datapoints based on a threshold from a first time period to a second time period;
and
initiate application of a drift policy on the plurality of datapoints based on a result of the determination of whether or not there has been a change.

1 more element

Dependencies are inferred from the claim text.

Node and methods performed thereby for handling drift in data

Life of this patent

Node and methods performed thereby for handling drift in data

Life of this patent

Abstract

Claims21