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@@ -37,10 +37,12 @@ With the experimental setup above, we evaluated the performance of RKME Image by |
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| Job Selector Reuse (Multiple) | 0.534 | |
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| Average Ensemble Reuse (Multiple) | 0.676 | |
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In some specific settings, the user will have a small number of labeled samples. In such settings, learning the weight of selected learnwares on a limited number of labeled samples can result in a better performance than training directly on a limited number of labeled samples. |
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### Labelled Sample Scenario |
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In some specific settings, the user will have a small number of labeled samples. In such settings, learning the weight of selected learnwares on a limited number of labeled samples can result in a better performance than training directly on a limited number of labeled samples. |
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<div align=center> |
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<img src="../../docs/_static/img/image_labeled.svg" alt="Results on Image Experimental Scenario" style="width:50%;" /> |
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</div> |
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</div> |
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Note that in labelled sample scenario, the labelled samples are repeatedly sampled 3 to 10 times, in order to reduce the estimation error in accuracy due to random sampling. |