Patents by Inventor Jane Sherman

Jane Sherman has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 10083263
    Abstract: Data can be accessed from a plurality of disparate data sources from at least one database. A plurality of test models can be automatically built by a model building engine. Each test model can have predetermined predictive variables. A final set of predictive variables can be determined by a variable selector from the predetermined predictive variables in the plurality of test models by comparing the predictive power of the predictive variables across the plurality of test models. A master dataset can be generated from the disparate data sources. A master model can be built from the master dataset. The master model can combine the final set of predictive variables from the plurality of disparate data sources. The master model can characterize a quantitative estimate of the probability that an entity will display a defined behavior. Related apparatus, systems, techniques, and articles are also described.
    Type: Grant
    Filed: October 2, 2017
    Date of Patent: September 25, 2018
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Lu Gao, Brendan Alexander Lacounte, Jane Sherman, Radha Chandra, Erik Franco, Ethan J. Dornhelm
  • Publication number: 20180025104
    Abstract: Data can be accessed from a plurality of disparate data sources from at least one database. A plurality of test models can be automatically built by a model building engine. Each test model can have predetermined predictive variables. A final set of predictive variables can be determined by a variable selector from the predetermined predictive variables in the plurality of test models by comparing the predictive power of the predictive variables across the plurality of test models. A master dataset can be generated from the disparate data sources. A master model can be built from the master dataset. The master model can combine the final set of predictive variables from the plurality of disparate data sources. The master model can characterize a quantitative estimate of the probability that an entity will display a defined behavior. Related apparatus, systems, techniques, and articles are also described.
    Type: Application
    Filed: October 2, 2017
    Publication date: January 25, 2018
    Applicant: FAIR ISAAC CORPORATION
    Inventors: Lu Gao, Brendan Alexander Lacounte, Jane Sherman, Radha Chandra, Erik Franco, Ethan J. Dornhelm
  • Patent number: 9779187
    Abstract: Data can be accessed from a plurality of disparate data sources from at least one database. A plurality of test models can be automatically built by a model building engine. Each test model can have predetermined predictive variables. A final set of predictive variables can be determined by a variable selector from the predetermined predictive variables in the plurality of test models by comparing the predictive power of the predictive variables across the plurality of test models. A master dataset can be generated from the disparate data sources. A master model can be built from the master dataset. The master model can combine the final set of predictive variables from the plurality of disparate data sources. The master model can characterize a quantitative estimate of the probability that an entity will display a defined behavior. Related apparatus, systems, techniques, and articles are also described.
    Type: Grant
    Filed: August 26, 2014
    Date of Patent: October 3, 2017
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Lu Gao, Brendan Alexander Lacounte, Jane Sherman, Radha Chandra, Erik Franco, Ethan J. Dornhelm
  • Patent number: D672465
    Type: Grant
    Filed: November 3, 2011
    Date of Patent: December 11, 2012
    Inventor: Constance Jane Sherman