18134059. MODEL-TIERING MACHINE LEARNING MODEL simplified abstract (International Business Machines Corporation)
Contents
MODEL-TIERING MACHINE LEARNING MODEL
Organization Name
International Business Machines Corporation
Inventor(s)
Ana Paula Appel of São Paulo (BR)
Paulo Rodrigo Cavalin of Rio de Janeiro (BR)
Graziella Martins Caputo of Katy TX (US)
Paula Fernanda Pereira of São Paulo (BR)
MODEL-TIERING MACHINE LEARNING MODEL - A simplified explanation of the abstract
This abstract first appeared for US patent application 18134059 titled 'MODEL-TIERING MACHINE LEARNING MODEL
The abstract of this patent application describes a method, system, and computer program product that involve receiving an input machine learning model, creating a feature vector based on metadata of the model and a data source, determining a risk tier for the model, and providing validation information based on the risk tier.
- Simplified Explanation:
This patent application introduces a process for assessing the risk level of a machine learning model and providing validation information based on that risk tier.
- Key Features and Innovation:
- Receiving an input machine learning model for deployment - Creating a feature vector using metadata and data source information - Classifying the model into predefined risk tiers - Providing validation information to an evaluator based on the risk tier
- Potential Applications:
- Quality control for machine learning models - Risk assessment in deploying machine learning models - Ensuring reliability and accuracy of machine learning applications
- Problems Solved:
- Lack of standardized risk assessment for machine learning models - Difficulty in validating machine learning models for production environments
- Benefits:
- Improved reliability of machine learning models - Enhanced validation process for deployment - Standardized risk assessment framework
- Commercial Applications:
"Machine Learning Model Risk Assessment and Validation System for Production Environments"
- Questions about Machine Learning Model Risk Assessment and Validation System:
1. How does this system improve the deployment process of machine learning models? - This system enhances the reliability and accuracy of machine learning models by providing a standardized risk assessment framework.
2. What are the key components of the feature vector used in determining the risk tier of a machine learning model? - The feature vector is based on metadata of the model and data source information, allowing for a comprehensive assessment of the model's risk level.
Original Abstract Submitted
A method, system, and computer program product are configured to: receive an input machine learning model being developed for deployment in a production environment; create a feature vector based on metadata of the input machine learning model and a data source used by the input machine learning model; determine a risk tier of the input machine learning model by classifying the input machine learning model into one of plural predefined tiers using the feature vector with a model-tiering machine learning model; and provide validation information to an evaluator wherein the validation information is based on the risk tier and is used to validate the input machine learning model in accordance with the risk tier.
