International business machines corporation (20240346387). MODEL-TIERING MACHINE LEARNING MODEL simplified abstract

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 20240346387 titled 'MODEL-TIERING MACHINE LEARNING MODEL

Simplified Explanation: This patent application describes a method, system, and computer program product that involve developing a machine learning model for deployment in a production environment, 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.

Key Features and Innovation:

• Development of a machine learning model for deployment in a production environment.
• Creation of a feature vector based on metadata of the model and a data source.
• Classification of the model into predefined risk tiers using a model-tiering machine learning model.
• Provision of validation information to an evaluator based on the risk tier.

Potential Applications: This technology could be applied in various industries where machine learning models are used, such as finance, healthcare, and marketing.

Problems Solved: This technology addresses the need for assessing the risk associated with deploying machine learning models in production environments.

Benefits:

• Improved validation process for machine learning models.
• Enhanced risk assessment for deployment in production environments.
• Increased efficiency in evaluating machine learning models.

Commercial Applications: Potential commercial applications of this technology include risk assessment services for machine learning model deployment, software tools for model validation, and consulting services for optimizing model deployment strategies.

Questions about Machine Learning Model Validation: 1. How does the feature vector contribute to determining the risk tier of a machine learning model? 2. What are the implications of using a model-tiering machine learning model for classifying risk tiers?

Frequently Updated Research: Stay informed about the latest advancements in machine learning model validation techniques and risk assessment methodologies to enhance the effectiveness of this technology.

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.