18241611. LEARNING DEVICE simplified abstract (NEC Corporation)
Contents
LEARNING DEVICE
Organization Name
Inventor(s)
Batnyam Enkhtaivan of Tokyo (JP)
LEARNING DEVICE - A simplified explanation of the abstract
This abstract first appeared for US patent application 18241611 titled 'LEARNING DEVICE
Simplified Explanation
The learning device described in the patent application includes an acquisition unit and a conversion unit. The acquisition unit takes in outputs from learners for each class received from another learning device, as well as outputs from learners trained by the own device, and acquires a specific output for each class. The conversion unit then performs a conversion process for each class to express a probability related to the acquired output for each class.
- Acquisition unit inputs outputs from learners for each class
- Acquisition unit acquires a specific output for each class
- Conversion unit expresses a probability related to the acquired output for each class
Potential Applications
This technology could be applied in various fields such as:
- Education
- Healthcare
- Finance
Problems Solved
This technology helps in:
- Improving learning outcomes
- Enhancing decision-making processes
- Increasing efficiency in data analysis
Benefits
The benefits of this technology include:
- Enhanced accuracy in predictions
- Better understanding of complex data
- Improved performance in various tasks
Potential Commercial Applications
Optimizing this technology for commercial use could lead to applications in:
- Predictive analytics software
- Personalized learning platforms
- Healthcare diagnostics systems
Unanswered Questions
== How does this technology handle large datasets efficiently? == What are the potential limitations of this technology in real-world applications?
Original Abstract Submitted
A learning device includes an acquisition unit and a conversion unit. The acquisition unit inputs thereto, for each class, an output of a learner for each class received from another learning device and an output of a learner for each class trained by the own device, and acquires a given output for each class. The conversion unit performs, for each class, a conversion process to express a probability with respect to the given output for each class acquired by the acquisition unit.
