Graphical user interface for rule-based filtering evaluation by computers

Abstract

1. Name of the product in this design: Graphical User Interface for Rule Filtering Evaluation for Computers. 2. Purpose of this design: This design is used to run programs. 3. The key design features of this product are the graphical user interface displayed on the computer. 4. The image or photograph that best illustrates the design points: Change state diagram 3. 5. Since computers are a current technology, rear view, left view, right view, top view, and bottom view are omitted. 6. Uses of the graphical user interface: In the field of machine learning, it provides users with the ability to filter samples according to rules and evaluate new rules. It supports users to flexibly call some rules to filter samples. On the other hand, based on the filtered samples, it conducts multiple rounds of effect verification on new rules, ultimately helping users to identify effective new rules. 7. Description of the changing states of the graphical user interface: The main view is the initial interface for the filtering rule set and the evaluation rule set. The top of the main view displays a list of rules used for filtering samples, and the bottom displays a list of rules used for evaluating and analyzing new rules. Clicking "Configuration" in the main view leads to Change State Figure 1. In Change State Figure 1, the user needs to complete two selections: first, select the filtering rule set; second, select the evaluation rule set. After completing these steps, the user proceeds to Change State Figure 2. Change State Figure 2 displays the basic effect information of the corresponding rules at the top. Clicking the "Calculate" button and selecting the target rules (multiple selections are possible) will automatically filter the samples, leading to Change State Figure 3. Change State Figure 3 simultaneously displays new effect indicators at the bottom. In the evaluation rule set area, a single rule will have multiple effect indicators added based on different sample quantities. The list is arranged in reverse chronological order of generation time, facilitating horizontal comparison and analysis. In the main view, users can click the star-shaped "favorite" icon next to a rule to save and collect the desired new rules based on the comprehensive effect indicators.

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