Rebalancing allows you to create a large number of relevant business scenarios out of the few that are present in your data. Use it to simulate what-if scenarios based on your existing, historical data, or make minority classes clearly visible for downstream machine learning algorithms.
| Rebalancing is only available for subject tables and can only be applied to a single column with the categorical encoding type. |
| Rebalancing cannot guarantee an increase in downstream model performance. Up or downsampling of a class in the original dataset only helps the downstream model in some instances. |
Follow these steps to rebalance your data
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Click Create synthetic data to begin |
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Download the Insurance policy dataset , upload it, and click Proceed |
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Click on the Data settings tab, scroll all the way down to find the age_bins column, and click on the cog icon to open the column settings drawer. |
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Configure the column settings like in the screenshot below and click Save when done. |
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Click Launch job to synthesize |
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