Kioxia corporation (20240095306). INFORMATION PROCESSING APPARATUS AND INFORMATION PROCESSING METHOD simplified abstract
Contents
- 1 INFORMATION PROCESSING APPARATUS AND INFORMATION PROCESSING METHOD
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 INFORMATION PROCESSING APPARATUS AND INFORMATION PROCESSING METHOD - 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
INFORMATION PROCESSING APPARATUS AND INFORMATION PROCESSING METHOD
Organization Name
Inventor(s)
Osamu Torii of Minato Tokyo (JP)
Shinichiro Manabe of Yokohama Kanagawa (JP)
INFORMATION PROCESSING APPARATUS AND INFORMATION PROCESSING METHOD - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240095306 titled 'INFORMATION PROCESSING APPARATUS AND INFORMATION PROCESSING METHOD
Simplified Explanation
The patent application describes an information processing apparatus that uses regression analysis to extract important variables influencing a target variable.
- The processing circuitry acquires both objective and explanatory variables for regression analysis.
- Through sparse modeling with regression equations, the apparatus identifies the most influential explanatory variables on the objective variable.
- It then further refines the analysis by identifying a second explanatory variable that has a high influence on the previously identified influential variables.
Potential Applications
This technology could be applied in various fields such as finance, marketing, and healthcare for predictive modeling and decision-making processes.
Problems Solved
This technology helps in identifying key variables that impact the target variable, leading to more accurate predictions and insights.
Benefits
The apparatus provides a systematic approach to analyzing data and extracting important variables, which can improve the efficiency and effectiveness of decision-making processes.
Potential Commercial Applications
With its ability to extract key variables from data, this technology could be valuable in industries such as banking, insurance, and retail for risk assessment, customer segmentation, and trend analysis.
Possible Prior Art
One possible prior art could be traditional regression analysis techniques used in various fields for predictive modeling and data analysis.
What are the specific industries that could benefit from this technology?
Industries such as finance, marketing, healthcare, and retail could benefit from this technology by improving their predictive modeling and decision-making processes.
How does this technology compare to traditional regression analysis methods?
This technology offers a more refined approach to regression analysis by identifying the most influential variables on the target variable, leading to more accurate predictions and insights compared to traditional methods.
Original Abstract Submitted
an information processing apparatus comprising processing circuitry. the processing circuitry is configured to acquire objective variables and explanatory variables which are regression analysis targets, extract a plurality of first explanatory variables having a high degree of influence on the objective variable from among the explanatory variables by sparse modeling using a first regression equation, and extract a second explanatory variable having a high degree of influence on the plurality of first explanatory variables by sparse modeling using a second regression equation.
