{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11977993","patent":{"patent_number":"US-11977993","title":"Data source correlation techniques for machine learning and convolutional neural models","assignee":null,"inventors":[],"filing_date":"2020-11-30T00:00:00.000Z","publication_date":"2024-05-07T00:00:00.000Z","cpc_codes":["G06N","G06N","G06N"],"num_claims":20,"abstract":"A data model computing device receives a first data model with a first set of attributes, a first margin of error, a first set of predictions, and an underlying data set. Subsequently, the data model computing device receives a second data model with a second set of attributes, as the test data for a machine learning module. Based on the first and second data model, the machine learning function generates a second set of predictions and a second margin of error. The data model computing device performs a statistical analysis on the first and second set of predictions and the first and second margin of error to determine if the second set of predictions converge with the first set of predictions and second margin of error is narrower than the first margin of error, to determine if the second data model improves the prediction results of the machine learning module."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Data source correlation techniques for machine learning and convolutional neural models","description":"A data model computing device receives a first data model with a first set of attributes, a first margin of error, a first set of predictions, and an underlying data set. Subsequently, the data model ","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11977993","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-11977993","citation_suggestion":"Patentable. \"Data source correlation techniques for machine learning and convolutional neural models\" (US-11977993). https://patentable.app/patents/US-11977993","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11977993","json":"https://patentable.app/api/llm-context/US-11977993","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T13:45:46.406Z"}