Evaluation Apparatus Using Category-Support Variable Segmentation
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Solution Overview
Problem
Evaluating an evaluation target using multiple indicators is often complex and inaccurate due to the large number of feature values generated when combining explanatory variables, making it difficult to comprehensively assess the target effectively.
Innovation Solution
An evaluation apparatus and method that acquire combination determination information to combine category variables with support variables, determining groups based on category variable values and generating evaluation information using statistics of support variables within these groups, thereby simplifying the evaluation process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple indicators are combined to comprehensively evaluate an evaluation target, then evaluation comprehensiveness is improved, but evaluation complexity increases
Solution Approach 1:
The patent segments the evaluation process by dividing multiple indicators into a category variable and support variables. The category variable serves as the primary classification dimension, while support variables provide detailed evaluation within each category. This segmentation allows comprehensive evaluation without requiring all indicators to be processed simultaneously, thereby reducing complexity while maintaining comprehensiveness.
2Adaptability or versatility
If multiple indicators are combined to comprehensively evaluate an evaluation target, then evaluation comprehensiveness is improved, but evaluation accuracy deteriorates
Solution Approach 1:
The patent introduces the category variable as an intermediary that mediates between multiple support variables and the final evaluation result. The category variable groups related support variables together, allowing the evaluation system to process multiple indicators systematically. This intermediary structure prevents information loss and maintains evaluation accuracy by organizing indicators in a hierarchical manner rather than treating them as a flat set.
3Productivity
If a large number of feature values are generated by combining explanatory variables, then data analysis capability is improved, but the number of feature values becomes too great
Solution Approach 1:
The patent applies segmentation by organizing the large set of generated feature values into groups based on the category variable. Instead of processing all feature values individually, the system segments them into manageable subsets associated with each category. This allows effective data analysis while controlling the computational burden by processing segmented data rather than the complete set of all possible feature values.
Data Source
AI summary
An evaluation apparatus includes a combination acquisition unit and an evaluation unit. The combination acquisition unit acquires combination determination information from an indicator selection apparatus. The combination determination information determines a combination of a category variable being one of a plurality of indicators related to an evaluation target and at least one support variable each being the indicator different from the category variable. Further, a plurality of groups are determined based on a value of the category variable. Then, a statistic of the support variable is generated for each of the plurality of groups. The evaluation unit generates, for each of the support variables, evaluation information, for example, an evaluation value by using a value of the support variable of the evaluation target and the statistic of the support variable of the group to which the value of the category variable of the evaluation target belongs.