MOSTLY AI lets you adjust the generation mood for each column in your data. This allows you to control the degree to which the synthetic version of the column will adhere to the detected distributions and correlations in the original data.
We recommend using this feature if you’re testing with healthcare data, which requires synthetic data with strong business rule adherence. But you can also use it to simulate human error—inputs that you might never see in the data but could happen.
The following generation mood settings are available:
| Conservative |
Generates synthetic data strictly within the business rules captured in the data. |
| Representative |
Generates synthetic data that adheres less strictly to the business rules captured in the data. |
| Creative |
Generates synthetic data skewed towards the outliers of the detected distributions. This option can be helpful when generating test data. |
Follow these steps to change the generation mood
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Click Create synthetic data to begin |
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Download the US Census dataset , upload it, and click Proceed |
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Click on the Data settings tab and then on the Edit multiple columns button. |
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Select all the columns, change the Generation mood to Creative, confirm, and click Return to column list button when done. |
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Click Launch job to synthesize |
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