Interactive adaptation of machine learning models for time series data
US12061632B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 19, 2022 |
| Grant date | Aug 13, 2024 |
| Priority date | — |
| Expiry date | May 20, 2042 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L43/08
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A computer-implemented method can comprise establishing programmatic connections to a digitally stored first database comprising over one million records, each of the records comprising time series data organized as an event with a timestamp and an event data, the first database being part of a HADOOP cluster that is programmatically coupled to a HIVE data warehouse manager and a PRESTO query engine, reading a configuration file that specifies one or more tables in the first database and for each particular table among the one or more tables, forming and submitting a plurality of PRESTO queries to the first database, each of the PRESTO queries specifying one or more data aggregation operations, and in response thereto, receiving a set of aggregated records of the first database, training a machine learning model using a portion of the aggregated records as a training dataset, determining a plurality of outlier values that are represented in the set of aggregated records, one or more change points that are represented in the set of aggregated records, a plurality of seasonality patterns that are represented in the set of aggregated records, receiving, from a second computer, input s…
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.