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@@ -34,7 +34,7 @@ In addition of accuracy (called here *exact accuracy*) in order to be robust to
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  $$\mathrm{top\!-\!2\; acc}=\frac{1}{|\mathcal{O}|}\sum_{i\in\mathcal{O}}\sum_{0\leq l < 2}\mathbb{1}(\hat{f}_{i,l}=y_i)$$
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- where $\hat{f}_l$ is the l-th largest predicted label, $y$ the true label, $\mathcal{O}$ is the test set of the observations and $\mathbb{1}$ is the indicator function.
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  | **class** | **exact accuracy (%)** | **top-2 acc (%)** | **support** |
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  | :---------: | :--------------------: | :---------------: | :---------: |
 
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  $$\mathrm{top\!-\!2\; acc}=\frac{1}{|\mathcal{O}|}\sum_{i\in\mathcal{O}}\sum_{0\leq l < 2}\mathbb{1}(\hat{f}_{i,l}=y_i)$$
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+ where \\(\hat{f}_l\\) is the l-th largest predicted label, \\(y\\) the true label, \\(\mathcal{O}\\) is the test set of the observations and \\(\mathbb{1}\\) is the indicator function.
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  | **class** | **exact accuracy (%)** | **top-2 acc (%)** | **support** |
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  | :---------: | :--------------------: | :---------------: | :---------: |