talk a bit more on quality
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@ -241,6 +241,13 @@ value being equal across all atributes suggests entire rows were
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removed, rather than select values from separate rows. The only
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exception is the `occupation` attribute, which was entirely removed.
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![Quality models](quality.png)
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The values for precision (Gen. Intensity) and Information Loss (Granularity)
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are high. The values for Discernibility and Average Equivalence Class Size
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are also high. And in general, all the quality models (both attribute-level
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and dataset-level) are high. Hence, we believe we've achieved a good utility.
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### Effect of parameters
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quality.png
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report.pdf
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