blended data

blended data

[¦blen·dəd ′dad·ə]
(engineering)
Q point that is the combination of scan data and track data to form a vector.
References in periodicals archive ?
D: Blended data. E and F: Images from the HoloLens headset enabling holographic visualisation ([C] 2018 AANS).
[W.sup.6.sub.1](O), [W.sup.6.sub.1](T), and [W.sup.6.sub.1](B) represent online, traditional, and blended data sets, respectively.
In addition, the numbers of best components for the online, traditional, and blended data sets were all equal to the numbers of independent variables for each data set, which shows that each data set required whole independent variables to determine the optimal predictive performance.
The blended data ARPU (2G+ 3G) also improved to ` 108 and usage per data subscriber is at 409 MB.
Blended data solutions already virtually dissolve traditional silos and provide creditors with additional insights.
Creditors are making much greater use of blended data, uniting business and personal financial information to allow credit managers to look beyond just a business' credit report or its owner's consumer credit report.
Based on research showing that blended scores--which include both personal and business data--capture 46% more small-business deterioration than commercial data alone, many of our clients opt to receive and evaluate blended data that takes into consideration the history of both the business and the business owner.
The idea behind blended data is simple: The more information you feed into a model, the more predictive it will be, and blended data gives creditors the best of both consumer and business information worlds.
Blended data combines the advantages of business credit scores, which are a leading indicator of credit payment issues for larger and older companies, with the advantages of consumer scores, which have a slight edge in predicting issues with the smallest and newest businesses, where the owners have not fully separated personal and business expenses.