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@@ -73,8 +73,7 @@ ds['pixel_values'][405]
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  <img src="https://huggingface.co/datasets/mpg-ranch/leafy_spurge/resolve/main/doc_figures/ground_truth_tile.png" width="39px" height="39px">
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  # Geographic splits within the training set
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- <!-- <img src="https://huggingface.co/datasets/mpg-ranch/leafy_spurge/resolve/main/doc_figures/train_clusters.png" width="75%" height="75%"> -->
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- <iframe src="https://huggingface.co/datasets/mpg-ranch/leafy_spurge/blob/main/doc_figures/train_map.html" width="700" height="450"></iframe>
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  We gathered ground truth at multiple sites and observations within a site were geographically clustered. We suggest using the cluster feature to establish holdout sets for cross-validated hyperparameter tuning. This will simluate model performance when classifying leafy spurge at new sites (such as those of the test set). You can filter by cluster metadata as follows:
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  <img src="https://huggingface.co/datasets/mpg-ranch/leafy_spurge/resolve/main/doc_figures/ground_truth_tile.png" width="39px" height="39px">
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  # Geographic splits within the training set
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+ <img src="https://huggingface.co/datasets/mpg-ranch/leafy_spurge/resolve/main/doc_figures/train_clusters.png" width="75%" height="75%">
 
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  We gathered ground truth at multiple sites and observations within a site were geographically clustered. We suggest using the cluster feature to establish holdout sets for cross-validated hyperparameter tuning. This will simluate model performance when classifying leafy spurge at new sites (such as those of the test set). You can filter by cluster metadata as follows:
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