Adaptive fuzzy fallback stratified sampling for fast reporting and forecasting
US9524510B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 2, 2013 |
| Grant date | Dec 20, 2016 |
| Priority date | — |
| Expiry date | May 17, 2035 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q30/0277
- WIPO fieldIT methods for management
- WIPO sectorElectrical engineering
Abstract
Techniques and mechanisms described herein facilitate adaptive fuzzy fallback stratified sampling. According to various embodiments, an actual or estimated minimum vertex cover of a feature dependency graph representing a dataset may be determined. The dataset may include a plurality of feature vectors and a plurality of features. Each feature vector may include a plurality of feature values that correspond with the features. The feature dependency graph may represent a plurality of conditional dependencies between the features. The minimum vertex cover may designate a subset of the features for strata selection. The feature vectors may be partitioned into a plurality of strata based on the designated subset of features. Each stratum may include one or more of the feature vectors. Each feature vector may be assigned to a corresponding stratum based on the values of the designated subset of features for the feature vector.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.