2.3 KiB
2.3 KiB
| 1 | # example_dataset.csv |
|---|---|
| 2 | # This is an example dataset for testing the ai-ethics-validator plugin. |
| 3 | # It contains sample data with features that might be relevant to fairness and ethical considerations. |
| 4 | # |
| 5 | # Columns: |
| 6 | # - ID: Unique identifier for each record. |
| 7 | # - Age: Age of the individual. |
| 8 | # - Gender: Gender of the individual (Male, Female, Other). |
| 9 | # - Income: Annual income of the individual. |
| 10 | # - Education: Highest level of education attained (e.g., High School, Bachelor's, Master's, PhD). |
| 11 | # - Location: Geographic location (e.g., Urban, Rural, Suburban). |
| 12 | # - Decision: The decision made by the AI system (e.g., Approved, Denied). This is the target variable. |
| 13 | # - Race: Race of the individual (e.g., White, Black, Asian, Hispanic, Other). Important for fairness analysis. |
| 14 | # |
| 15 | # Note: This is synthetic data and does not represent any real individuals. |
| 16 | # Replace this with your actual dataset for real-world validation. |
| 17 | # |
| 18 | # To use this dataset with the plugin, ensure it is accessible to the plugin's environment. |
| 19 | ID,Age,Gender,Income,Education,Location,Decision,Race |
| 20 | 1,25,Male,50000,Bachelor's,Urban,Approved,White |
| 21 | 2,32,Female,60000,Master's,Suburban,Approved,Black |
| 22 | 3,48,Male,75000,PhD,Urban,Approved,Asian |
| 23 | 4,28,Female,45000,High School,Rural,Denied,Hispanic |
| 24 | 5,35,Male,55000,Bachelor's,Suburban,Approved,White |
| 25 | 6,41,Female,70000,Master's,Urban,Approved,Black |
| 26 | 7,22,Male,30000,High School,Rural,Denied,White |
| 27 | 8,50,Female,80000,PhD,Suburban,Approved,Asian |
| 28 | 9,29,Male,52000,Bachelor's,Urban,Approved,Hispanic |
| 29 | 10,38,Female,65000,Master's,Rural,Denied,Black |
| 30 | 11,26,Male,48000,High School,Suburban,Denied,White |
| 31 | 12,45,Female,72000,PhD,Urban,Approved,Asian |
| 32 | 13,31,Male,58000,Bachelor's,Rural,Approved,Hispanic |
| 33 | 14,23,Female,35000,High School,Urban,Denied,Black |
| 34 | 15,55,Male,90000,Master's,Suburban,Approved,White |
| 35 | 16,40,Female,68000,PhD,Rural,Approved,Asian |
| 36 | 17,27,Male,51000,Bachelor's,Urban,Approved,Hispanic |
| 37 | 18,34,Female,62000,Master's,Suburban,Approved,Black |
| 38 | 19,49,Male,78000,PhD,Rural,Approved,White |
| 39 | 20,30,Female,46000,High School,Urban,Denied,Asian |
| 40 | 21,24,Male,32000,High School,Rural,Denied,Hispanic |
| 41 | 22,52,Female,85000,PhD,Suburban,Approved,Black |
| 42 | 23,37,Male,60000,Bachelor's,Urban,Approved,White |
| 43 | 24,43,Female,74000,Master's,Rural,Approved,Asian |
| 44 | 25,21,Male,28000,High School,Suburban,Denied,Hispanic |
| 45 | # Add more rows as needed. Ensure sufficient diversity in the data. |