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@@ -31,7 +31,9 @@ Evaluation results
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  In addition of accuracy (called here *exact accuracy*) in order to be robust to +/-1 star estimation errors, we will take the following definition as a performance measure:
 
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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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  In addition of accuracy (called here *exact accuracy*) in order to be robust to +/-1 star estimation errors, we will take the following definition as a performance measure:
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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** |