Interactive Decision Tree Modification via Node Split Adjustment
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Solution Overview
Problem
Current decision tree implementations lack an intuitive approach for users to modify node splits based on real-world constraints and objectives, such as regulatory, deployment, and computing infrastructure considerations, which are not accounted for during the automatic building process.
Innovation Solution
A method and system that allow users to adjust node split parameters, including features, fit functions, and values, through a graphical user interface, enabling users to control decision tree growth according to their specific constraints and objectives, and dynamically modify the decision tree based on user selections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional decision tree fitting is used with automatic node splitting, then the decision tree can be built quickly based on statistical accuracy, but the model cannot accommodate real-world constraints and objectives such as regulatory, deployment, and computing infrastructure considerations
Solution Approach 1:
The patent introduces an intermediary user interface that mediates between the automatic decision tree building process and user constraints. This interface allows users to specify constraints and objectives without requiring them to understand or modify the complex underlying algorithms, thus adding adaptability while maintaining system simplicity.
Solution Approach 2:
The system dynamically adjusts the node splitting process based on user-specified constraints. Instead of a fixed automatic process, the system adapts its behavior in real-time based on user input, allowing the decision tree to be modified after initial construction to meet real-world requirements.
2Adaptability or versatility
If users are allowed to manually adjust node split parameters, then the model can be customized to meet specific objectives and constraints, but the ease of operation decreases due to the complexity of modifying decision tree parameters
Solution Approach 1:
The user interface acts as an intermediary that simplifies the complex task of adjusting node split parameters. Users interact with high-level constraints and objectives rather than directly manipulating complex algorithmic parameters, making the system easier to operate while maintaining customization capability.
Solution Approach 2:
The system creates simplified representations or copies of the decision tree structure that users can interact with. Instead of requiring users to work with the full complexity of the original model, the interface provides a simplified view that preserves essential information while reducing operational complexity.
3Ease of operation
If the decision tree is built using automatic algorithms without user input, then the process is fast and simple to operate, but the model cannot reflect stakeholder objectives and constraints
Solution Approach 1:
The system performs preliminary automatic decision tree building to establish a baseline model quickly. This preliminary action preserves the speed and simplicity of automatic model building while creating a foundation that can later be enhanced with stakeholder constraints through user input.
Solution Approach 2:
The system implements a feedback mechanism where users can review the automatically generated decision tree and provide constraints and objectives. The system then uses this feedback to refine and adjust the model, ensuring that stakeholder information is incorporated without sacrificing the initial efficiency of automatic building.
Data Source
AI summary
An approach is provided in which a method, system, and program product display, on a user interface, at least one of a set of node split parameters in response to receiving a first user selection that selects a node in a decision tree. The selected node branches to a set of child nodes in the decision tree based on the set of node split parameters. The method, system, and program product adjust at least one of the set of node split parameters of the selected node in response to receiving a second user selection. The method, system, and program product modify the decision tree based on the adjusted set of node split parameters. The modified decision tree includes a modified set of child nodes that branch from the selected node based on the adjusted set of node split parameters.