Systems and methods for machine learning using classifying, clustering, and grouping time series data
US10169720B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 16, 2016 |
| Grant date | Jan 1, 2019 |
| Priority date | — |
| Expiry date | Dec 16, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2216/03
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods are provided for performing data mining and statistical learning techniques on a big data set. More specifically, systems and methods are provided for linear regression using safe screening techniques. Techniques may include receiving a plurality of time series included in a prediction hierarchy for performing statistical learning to develop an improved prediction hierarchy. It may include pre-processing data associated with each of the plurality of time series, wherein the pre-processing includes tasks performed in parallel using a grid-enabled computing environment. For each time series, the system may determine a classification for the individual time series, a pattern group for the individual time series, and a level of the prediction hierarchy at which the each individual time series comprises an need output amount greater than a threshold amount. The computing system may generate an additional prediction hierarchy using the first prediction hierarchy, the classification, the pattern group, and the level.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.