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  <head>
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  <meta charset="utf-8" />
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  <meta name="viewport" content="width=device-width" />
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- <title>My static Space</title>
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  <link rel="stylesheet" href="style.css" />
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  <link href="https://fonts.googleapis.com/css2?family=Source+Sans+Pro:ital,wght@0,200;0,300;0,400;0,600;0,700;0,900;1,200;1,300;1,400;1,600;1,700;1,900&amp;display=swap" rel="stylesheet">
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  The full list of transforms supported by MLTest can be found in the <a href="https://docs.lakera.ai/configuration/robustness">documentation</a>.
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  </p>
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  <p>
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- <b>Fairness tests</b>: TODO
 
 
 
 
 
 
 
 
 
 
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  </p>
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  </div>
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  <head>
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  <meta charset="utf-8" />
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  <meta name="viewport" content="width=device-width" />
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+ <title>MLTest Demo</title>
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  <link rel="stylesheet" href="style.css" />
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  <link href="https://fonts.googleapis.com/css2?family=Source+Sans+Pro:ital,wght@0,200;0,300;0,400;0,600;0,700;0,900;1,200;1,300;1,400;1,600;1,700;1,900&amp;display=swap" rel="stylesheet">
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  <link href="https://fonts.googleapis.com/css2?family=IBM+Plex+Mono:wght@400;600;700&amp;display=swap" rel="stylesheet">
 
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  The full list of transforms supported by MLTest can be found in the <a href="https://docs.lakera.ai/configuration/robustness">documentation</a>.
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  </p>
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  <p>
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+ <b>Fairness tests</b>: these tests measure how fair your model is. That means, whether its performance is dependent
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+ on a protected attribute of a person. In this dataset, the age and gender of a subject may be considered
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+ protected attributes.
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+ </p>
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+ <p>
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+ We used two types of fairness tests on the age and gender of a person.
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+ The <code>Equalized Odds</code> ...
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+ The <code>Predictive Equality</code> ...
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+ </p>
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+ <p>
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+ More fairness tests supported by MLTest can be found in the <a href="https://docs.lakera.ai/configuration/fairness">documentation</a>
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  </p>
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  </div>
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