Predictive machine learning models
US10510009B1 · kind B1 · utility
Assignee
Inventor
Key dates
| Filing date | Jul 8, 2019 |
| Grant date | Dec 17, 2019 |
| Priority date | — |
| Expiry date | Jul 8, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q40/03
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and applying a machine learning model. One of the methods includes the actions of obtaining a collection of training data, the training data comprising collection of data points associated with a labeled set of real property parcels; training a machine learning model using the training data, the machine learning model being trained to generate a likelihood with respect to a parameter from input data associated with a specific parcel of real property, wherein training includes optimizing the model using a Markov chain optimization that seeks to minimize error in the model where the model is underpinned by one or more non-differentiable functions; receiving a plurality of data points associated with an input parcel of real property; and using the optimized model to generate a likelihood for the parameter for the input parcel of real property.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.