Pair-Wise Interaction Detection for Large Variable Sets

Solution Overview

Problem

Manual examination of pair-wise interaction effects among a large number of variables is infeasible due to the exponential increase in potential interactions, making it time- and processor-intensive, especially when dealing with thousands of unpreprocessed variables in regression models.

Innovation Solution

A computer-implemented method that groups variable values into predetermined groups, analyzes interactions between these groups to determine interaction scores, and identifies the most significant pairs of variables with the highest interaction scores, reducing computational intensity and enabling efficient detection of pair-wise interactions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual examination of pair-wise interaction effects is performed among a large number of variables, then detection accuracy is improved, but processing time and computational resources increase exponentially

Engineering Contradiction:

Improvedetection accuracyVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent segments the large set of variables into smaller groups based on their relationships and interaction patterns. By dividing the comprehensive variable set into manageable segments, the system can perform manual or detailed examination on each segment separately, maintaining detection accuracy while significantly reducing the overall processing time and computational resources required.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent performs preliminary actions by pre-processing variables to identify and filter out those with low potential for interaction before conducting detailed pair-wise analysis. This preliminary filtering step reduces the number of variable pairs that require intensive examination, thereby decreasing processing time while preserving the ability to detect significant interaction effects accurately.

Inventive Principle:

Principle #10Preliminary action

2Measurement precision

If manual examination of pair-wise interaction effects is performed among a large number of variables, then detection accuracy is improved, but computational resources increase exponentially

Engineering Contradiction:

Improvedetection accuracyVSAvoidcomputational resources

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The patent segments the large set of variables into smaller groups based on their relationships and interaction patterns. By dividing the comprehensive variable set into manageable segments, the system can perform manual or detailed examination on each segment separately, maintaining detection accuracy while significantly reducing the overall processing time and computational resources required.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent performs preliminary actions by pre-processing variables to identify and filter out those with low potential for interaction before conducting detailed pair-wise analysis. This preliminary filtering step reduces the number of variable pairs that require intensive examination, thereby decreasing processing time while preserving the ability to detect significant interaction effects accurately.

Inventive Principle:

Principle #10Preliminary action

3Reliability

If all pair-wise interaction effects among thousands of variables are analyzed, then completeness of detection is improved, but device complexity increases

Engineering Contradiction:

Improvecompleteness of detectionVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent segments the large set of variables into smaller groups based on their relationships and interaction patterns. By dividing the comprehensive variable set into manageable segments, the system can perform manual or detailed examination on each segment separately, maintaining detection accuracy while significantly reducing the overall processing time and computational resources required.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent performs preliminary actions by pre-processing variables to identify and filter out those with low potential for interaction before conducting detailed pair-wise analysis. This preliminary filtering step reduces the number of variable pairs that require intensive examination, thereby decreasing processing time while preserving the ability to detect significant interaction effects accurately.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20240160696A1Method for Automatic Detection of Pair-Wise Interaction Effects Among Large Number of Variables

Publication Date: 2024.05.16 STATE FARM MUTAL AUTOMOBILE INSURANCE COMPANY

AI summary

Techniques for automatically detecting pair-wise interaction effects among a large number of variables are provided. An example method includes obtaining a data set including data related to a target variable and each of a plurality of variables upon which the target variable depends; grouping the data related to each variable, of the plurality of variables, into a pre-determined number of groups of grouped variable values; analyzing the grouped variable values related to each variable as compared to the grouped variable values related to each other variable, of the plurality of variables, in order to determine a grouped variable interaction score for each pair of variables, of the plurality of variables; and identifying a pre-determined number of pairs of variables having the highest interaction scores, based on the grouped variable interaction score for each pair of variables.