18305712. METHOD AND ELECTRONIC DEVICE FOR AUTOMATED MACHINE LEARNING MODEL RETRAINING simplified abstract (SAMSUNG ELECTRONICS CO., LTD.)
Contents
METHOD AND ELECTRONIC DEVICE FOR AUTOMATED MACHINE LEARNING MODEL RETRAINING
Organization Name
Inventor(s)
Sukhdeep Singh of Bangalore (IN)
Joseph Thaliath of Bangalore (IN)
Ganesh Kumar Thangavel of Bangalore (IN)
METHOD AND ELECTRONIC DEVICE FOR AUTOMATED MACHINE LEARNING MODEL RETRAINING - A simplified explanation of the abstract
This abstract first appeared for US patent application 18305712 titled 'METHOD AND ELECTRONIC DEVICE FOR AUTOMATED MACHINE LEARNING MODEL RETRAINING
Simplified Explanation
The patent application describes a system and method for automated machine learning (ML) model retraining by an electronic device. The system and method involve running a first ML model and a second ML model, predicting the accuracy degradation of the first ML model using the second ML model, determining if the predicted accuracy degradation meets a pre-defined threshold, and retraining the first ML model when the predicted accuracy degradation meets the threshold.
- The system and method involve using two ML models, one as the primary model and the other as a predictor of accuracy degradation.
- The second ML model predicts the accuracy degradation of the first ML model.
- The system determines if the predicted accuracy degradation meets a pre-defined threshold.
- If the predicted accuracy degradation meets the threshold, the first ML model is retrained.
Potential applications of this technology:
- Automated retraining of ML models can be used in various industries such as finance, healthcare, and manufacturing.
- It can be applied in fraud detection systems to continuously improve accuracy and adapt to new fraud patterns.
- In healthcare, it can be used to retrain ML models for disease diagnosis and treatment recommendations based on new data.
Problems solved by this technology:
- ML models can experience accuracy degradation over time due to changes in data patterns or new data.
- Manual retraining of ML models can be time-consuming and resource-intensive.
- This technology automates the process of detecting accuracy degradation and retraining ML models, reducing the need for manual intervention.
Benefits of this technology:
- Continuous improvement of ML model accuracy by automatically retraining when accuracy degradation is predicted.
- Reduction in manual effort and resources required for ML model retraining.
- Increased efficiency and effectiveness of ML models in various applications.
Original Abstract Submitted
A system and/or method for automated ML model retraining by an electronic device. The system and/or method may include one or more of: running a first ML model and a second ML model, predicting an accuracy degradation of the first ML model using the second ML model, determining whether the predicted accuracy degradation meets a pre-defined threshold, and/or retraining the first ML model when the predicted accuracy degradation meets the pre-defined threshold.
