Pre-processing for data-driven model creation
AssigneeSparkcognition, Inc.
InventorsSari Andoni, Keith D. Moore, Syed Mohammad Amir Husain
Life of this patent
Estimating the term…
Abstract
A method includes receiving input that identifies one or more data sources and determining, based on the input, a machine learning problem type of a plurality of machine learning problem types supported by an automated model building (AMB) engine. The method also includes generating an input data set of the AMB engine based on application of one or more rules to the one or more data sources. The method further includes, based on the input data set and the machine learning problem type, initiating execution of the AMB engine to generate a neural network configured to model at least a portion of the input data set.
Claims20
A method comprising:
- receiving, at a processor of a computing device, input that identifies one or more data sources;
- determining, based on the input, a machine learning problem type of a plurality of machine learning problem types supported by an automated model building (AMB) engine;
- generating an input data set for the AMB engine including extracting first data values from the one or more data sources and modifying the first data values to generate second data values based on application of one or more rules, wherein the second data values include at least one value that is not present in the first data values;
- and
- based on the input data set and the machine learning problem type, initiating execution of the AMB engine to generate a neural network configured to model at least a portion of the input data set.
A computer system comprising:
- an automated model building (AMB) pre-processor configured to:
- receive input that identifies one or more data sources;
- determine a machine learning problem type of a plurality of machine learning problem types supported by an AMB engine;
- generate an input data set for the AMB engine including extracting first data values from the one or more data sources and modifying the first data values to generate second data values based on application of one or more rules, wherein the second data values include at least one value that is not present in the first data values;
- and
- based on the input data set and the machine learning problem type, initiate execution of the AMB engine to generate a neural network configured to model at least a portion of the input data set.
A computer-readable storage device storing instructions that, when executed, cause a computer to perform operations comprising:
- receiving input that identifies one or more data sources;
- determining, based on the input, a machine learning problem type of a plurality of machine learning problem types supported by an automated model building (AMB) engine;
- generating an input data set for the AMB engine including extracting first data values from the one or more data sources and modifying the first data values to generate second data values based on application of one or more rules, wherein the second data values include at least one value that is not present in the first data values;
- and
- based on the input data set and the machine learning problem type, initiating execution of the AMB engine to generate a neural network configured to model at least a portion of the input data set.
Dependencies are inferred from the claim text.