View source for 18551201. MACHINE LEARNING DEVICE, DEGREE OF SEVERITY PREDICTION DEVICE, MACHINE LEARNING METHOD, AND DEGREE OF SEVERITY PREDICTION METHOD simplified abstract (Mitsubishi Electric Corporation)

=MACHINE LEARNING DEVICE, DEGREE OF SEVERITY PREDICTION DEVICE, MACHINE LEARNING METHOD, AND DEGREE OF SEVERITY PREDICTION METHOD=


==Organization Name==

[[:Category:Mitsubishi Electric Corporation|Mitsubishi Electric Corporation]]


[[Category:Mitsubishi Electric Corporation]]

==Inventor(s)==

[[:Category:Ippei Nishimoto of Tokyo (JP)|Ippei Nishimoto of Tokyo (JP)]][[Category:Ippei Nishimoto of Tokyo (JP)]]

==MACHINE LEARNING DEVICE, DEGREE OF SEVERITY PREDICTION DEVICE, MACHINE LEARNING METHOD, AND DEGREE OF SEVERITY PREDICTION METHOD - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18551201 titled 'MACHINE LEARNING DEVICE, DEGREE OF SEVERITY PREDICTION DEVICE, MACHINE LEARNING METHOD, AND DEGREE OF SEVERITY PREDICTION METHOD

==Simplified Explanation==

The abstract describes a machine learning device capable of accurately predicting the degree of severity based on a situation, specifically in software development.

* Learning unit configured to learn the severity of problem solving for a target component item based on a dataset associating determination data regarding risk with a problem that occurred in software development.
* State variables regarding the risk are also considered in the learning process.

== Potential Applications ==
This technology could be applied in various industries where predicting the severity of a problem is crucial, such as healthcare, finance, and manufacturing.

== Problems Solved ==
This technology helps in accurately predicting the severity of a problem, allowing for proactive measures to be taken to mitigate risks and prevent potential issues.

== Benefits ==
- Improved risk management
- Enhanced problem-solving capabilities
- Increased efficiency in problem resolution

== Potential Commercial Applications ==
- Risk assessment software
- Problem severity prediction tools
- Software development optimization solutions

== Possible Prior Art ==
One possible prior art could be predictive analytics tools used in various industries to forecast outcomes based on historical data.

=== What data sets are used in the learning process? ===
The abstract mentions that the learning unit learns from a dataset that associates determination data regarding risk with a problem that occurred in software development. However, it does not specify the exact nature or sources of these datasets.

=== How accurate are the predictions made by this machine learning device? ===
The abstract does not provide information on the accuracy rates or performance metrics of the predictions made by this machine learning device. Additional details on the accuracy and reliability of the predictions would be helpful for potential users or investors.


==Original Abstract Submitted==

An object of the present disclosure is to provide a machine learning device, a degree of severity prediction device, and a machine learning method capable of accurately predicting the degree of severity based on a situation. The machine learning device according to the present disclosure includes a learning unit configured to learn a degree of severity of problem solving for a target component item based on a data set that associates determination data regarding a risk of the target component item with a problem that has occurred in software development and state variables regarding the risk.



[[Category:G06N20/00]]
[[Category:G06F8/77]]