Patent ID: 11961005
Assignee: STORYTELLERS.AI LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method for managing machine learning models in a network using one or more processors to execute instructions that are configured to cause actions, comprising:
determining a plurality of domain items based on domain data and associated schema information;
generating one or more labels that correspond to a predicted outcome based on the domain data, wherein each label is associated with one or more code blocks, and wherein execution of each code block selects a portion of the plurality of domain items having an association with the predicted outcome;
training a model based on a portion of a plurality of feature records and the one or more labels, wherein each feature record is associated with an observance of a domain item; and
disqualifying the trained model based on one or more evaluation metrics that are below a threshold value, wherein the disqualification causes further actions, including:
submitting one or more other portions of the plurality of feature records to the disqualified model, wherein the one or more other portions of feature records exclude the portion of feature records used to train the model;
determining one or more erroneous feature fields in the plurality of feature records based on one or more metrics associated with the submission of the one or more other portions of the plurality of feature records;
updating the plurality of feature records to exclude the one or more erroneous feature fields; and
retraining the disqualified model based on the plurality of updated feature records.