Predictive modeling
US8738549B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 19, 2011 |
| Grant date | May 27, 2014 |
| Priority date | — |
| Expiry date | May 21, 2032 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A predictive analysis generates a predictive model (Padj(Y|X)) based on two separate pieces of information, The predictive analysis begins by generating a base model distribution (Pgen(Y|X)) from the original training data set (Dorig) containing tuples (x,y) of indicators (x) and corresponding labels (y). Using the “true” distribution (Ptrue(X)) of indicators, a random data set (D′) of indicator records (x) is generated reflecting this “true” distribution (Ptrue(X)). Subsequently, the base model (Pgen(Y|X)) is applied to said random data set (D′), thus assigning a label (y) or a distribution of labels to each indicator record (x) in said random data set (D′) and generating an adjusted training set (Dadj). Finally, an adjusted predictive model (Padj(Y|X)) is trained based on said adjusted training set (Dadj).
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.