Nec corporation (20240119357). ANALYSIS DEVICE, ANALYSIS METHOD, AND NON-TRANSITORY COMPUTER-READABLE MEDIUM HAVING PROGRAM STORED THEREON simplified abstract
Contents
- 1 ANALYSIS DEVICE, ANALYSIS METHOD, AND NON-TRANSITORY COMPUTER-READABLE MEDIUM HAVING PROGRAM STORED THEREON
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 ANALYSIS DEVICE, ANALYSIS METHOD, AND NON-TRANSITORY COMPUTER-READABLE MEDIUM HAVING PROGRAM STORED THEREON - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
ANALYSIS DEVICE, ANALYSIS METHOD, AND NON-TRANSITORY COMPUTER-READABLE MEDIUM HAVING PROGRAM STORED THEREON
Organization Name
Inventor(s)
ANALYSIS DEVICE, ANALYSIS METHOD, AND NON-TRANSITORY COMPUTER-READABLE MEDIUM HAVING PROGRAM STORED THEREON - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240119357 titled 'ANALYSIS DEVICE, ANALYSIS METHOD, AND NON-TRANSITORY COMPUTER-READABLE MEDIUM HAVING PROGRAM STORED THEREON
Simplified Explanation
The abstract describes an analysis device, method, and program for identifying factors of prediction errors in prediction models. The device includes a metric evaluation unit and a factor identification unit to evaluate metrics and identify error factors, respectively.
- Metric evaluation unit calculates and evaluates various metrics related to prediction models and data used in the model.
- Factor identification unit identifies factors contributing to prediction errors based on the evaluation results of the metrics.
Potential Applications
This technology could be applied in various fields such as finance, healthcare, marketing, and weather forecasting to improve the accuracy of prediction models.
Problems Solved
This technology helps in easily identifying factors causing prediction errors, allowing for quick adjustments and improvements to prediction models.
Benefits
The benefits of this technology include enhanced accuracy of predictions, improved decision-making based on predictions, and increased efficiency in model optimization.
Potential Commercial Applications
One potential commercial application of this technology could be in the financial sector for optimizing investment strategies based on accurate predictions.
Possible Prior Art
One possible prior art could be the use of statistical analysis tools to identify factors affecting prediction errors in models.
What are the potential limitations of this technology in real-world applications?
One potential limitation of this technology in real-world applications could be the complexity of interpreting the evaluation results of various metrics and accurately identifying the factors contributing to prediction errors.
How does this technology compare to existing methods for identifying prediction errors in models?
This technology offers a more comprehensive approach by evaluating multiple types of metrics and considering various viewpoints to identify factors of prediction errors, which may lead to more accurate and efficient error identification compared to existing methods.
Original Abstract Submitted
provided are an analysis device, an analysis method, and a program capable of easily identifying a factor of a prediction error in prediction using a prediction model on the basis of various viewpoints. an analysis device () includes: a metric evaluation unit () that calculates and evaluates a plurality of types of metrics with respect to a prediction model, data of explanatory variables used in the prediction model, or data of target variables used in the prediction model; and a factor identification unit () that identifies a factor of an error in prediction by the prediction model according to a combination of evaluation results of the plurality of types of metrics.
