Series-Data Binary Classification With Dynamic Score Thresholds
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Solution Overview
Problem
Existing class classification methods require sequential data acquisition and repeated determinations until a predetermined condition is met, lacking the ability to dynamically adjust the balance between classification accuracy and time required.
Innovation Solution
A determination device and method that includes an acquisition unit, score calculation unit, threshold value determining unit, and class determination unit to dynamically adjust the relationship between classification accuracy and time by using integrated scores and threshold values for binary classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sequential data acquisition and repeated determination are performed until a predetermined condition is met, then classification accuracy is improved, but the time required for classification increases
Solution Approach 1:
The patent implements dynamic adjustment of the number of data points N used for classification based on the characteristics of the input signal. The system determines an appropriate N value adaptively rather than using a fixed value, allowing the classification process to balance accuracy and time requirements dynamically according to the specific input conditions
Solution Approach 2:
The patent changes the parameter N (number of data points) based on the slope characteristics of the input signal. By adjusting N according to the signal's rate of change, the system optimizes the trade-off between using sufficient data for accurate classification and minimizing the time required for classification
2Productivity
If a fixed number of data points are used for classification, then the classification process is simple and fast, but the classification accuracy cannot be dynamically adjusted
Solution Approach 1:
The system transitions from fixed-parameter classification to dynamic parameter adjustment by adapting the number of data points N based on real-time signal characteristics, enabling both speed and adaptability
Solution Approach 2:
The system uses feedback from the signal slope calculation to adjust the number of data points N. By continuously monitoring the input signal characteristics and adjusting N accordingly, the system achieves adaptive classification that responds to changing conditions
Data Source
AI summary
A determination device includes an acquisition unit that sequentially acquires a plurality of elements included in series data related to a classification target, a score calculation unit that calculates an integrated score for binary classification of the classification target each time the acquisition unit acquires the elements, a threshold value determining unit that determines an upper limit threshold value and a lower limit threshold value of the integrated score each time the acquisition unit acquires the elements, and a class determination unit that determines a determination result of the binary classification as one of a first class, a second class, and class indetermination, on the basis of comparison between the integrated score and the upper limit threshold value and the lower limit threshold value each time the acquisition unit acquires the elements.