Automated Exploratory Data Analysis Using Statistical Templates
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Solution Overview
Problem
Manual exploratory data analysis for machine learning model preparation is time-consuming and requires significant effort from expert users due to the need for manual inspection of large and complex datasets, which hampers the efficiency of feature engineering and model accuracy.
Innovation Solution
An automated exploratory data analysis system that selects statistical analysis tools, determines patterns, and applies natural language models to generate textual explanations, reducing the need for manual inspection by automatically analyzing datasets and providing insights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual inspection of the dataset is performed by expert users, then the analysis can be conducted with appropriate judgment and flexibility, but the process becomes time-consuming and requires significant effort
Solution Approach 1:
The system performs self-service by automatically executing statistical analysis algorithms on the dataset without requiring manual intervention. The automated EDA system selects and applies appropriate statistical tools, determines patterns, and generates explanations independently, eliminating the need for expert users to manually inspect the data while maintaining analysis quality.
Solution Approach 2:
The patent replaces the mechanical manual inspection process with an automated computational system. Instead of human experts manually reviewing data, the system uses statistical analysis algorithms, pattern recognition, and natural language generation to automatically perform the same analytical functions, thereby reducing time consumption while maintaining analytical rigor.
2Ease of operation
If manual inspection of the dataset is performed by expert users, then the analysis can be conducted with appropriate judgment and flexibility, but the process requires significant effort from expert users
Solution Approach 1:
The system performs self-service by automatically executing statistical analysis algorithms on the dataset without requiring manual intervention. The automated EDA system selects and applies appropriate statistical tools, determines patterns, and generates explanations independently, eliminating the need for expert users to manually inspect the data while maintaining analysis quality.
Solution Approach 2:
The patent replaces the mechanical manual inspection process with an automated computational system. Instead of human experts manually reviewing data, the system uses statistical analysis algorithms, pattern recognition, and natural language generation to automatically perform the same analytical functions, thereby reducing time consumption while maintaining analytical rigor.
3Loss of time
If automated analysis is implemented, then the time and effort for data analysis are reduced, but the system complexity increases
Solution Approach 1:
The automated EDA system is segmented into distinct functional modules: statistical analysis algorithm selection, data pattern determination, and natural language explanation generation. Each module handles a specific aspect of the analysis process independently, making the overall complex system manageable and easier to implement while maintaining automation benefits.
Solution Approach 2:
The system uses predefined templates as intermediaries between the statistical analysis results and the final explanations. These templates serve as a bridge that translates complex statistical findings into understandable natural language without requiring the system to generate explanations from scratch, simplifying the overall architecture.
4Ease of manufacture
If predefined templates are used for explanations, then the explanation generation process is simplified, but the adaptability to unique data patterns may be limited
Solution Approach 1:
The explanation generation system is made dynamic by allowing the selection and modification of predefined templates based on the specific patterns detected in the data. The system can adaptively choose different templates or adjust template parameters to match unique data characteristics, maintaining both simplicity and adaptability in the explanation generation process.
Data Source
AI summary
In an embodiment, a statistical analysis tool is applied on a first set of datapoints related to a first variable associated with a dataset. Based on the application of the statistical analysis tool, statistical information related to the first variable is determined. A set of patterns associated with the first set of datapoints is determined, based on the determined statistical information. Thereafter, a first set of predefined templates associated with the determined set of patterns is determined. Further, a natural language model is applied on the retrieved first set of predefined templates and on the determined statistical information. A first textual explanation of the determined set of patterns is determined, based on the application of the natural language model on the retrieved first set of predefined templates and on the determined statistical information. Further, the determined first textual explanation is rendered on a display device.