mindsponge.metrics
API Name |
Description |
Supported Platforms |
Balanced MSE error Compute Balanced MSE error between the prediction and the ground truth to solve unbalanced labels in regression task. |
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Focal error for Binary classifications. |
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Focal error for multi-class classifications. |
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Backbone FAPE Loss using frame_aligned_point_error_map function. |
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Flat-bottom loss to penalize structural violations between residues. |
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This is a loss penalizing any steric clashes due to non bonded atoms in different peptides coming too close. |
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Find optimal renaming of ground truth based on the predicted positions. |
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Measure point error under different alignments which computes error between two structures with B points under A alignments derived from the given pairs of frames. |
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Measure point error under different alignments which computes error between two structures with B points under A alignments derived from the given pairs of frames. |
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Computes several checks for structural violations. |
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Compute true and predicted distance matrices for \(C\alpha\). |
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sidechain FAPE Loss which take all local frames (side-chain, backbone) into consideration. |
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Computes loss for direct chi angle supervision. |
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Loss to penalize steric clashes within residues. |
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