Improvements to Single Evaluation SIDT Generation#41
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mjohnson541 merged 21 commits intomainfrom Mar 31, 2026
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…hicDecisionTree level
before we fit rules for the whole tree at the end, but this precluded more intelligent node selection algorithms
this algorithm prunes the tree based on an interpolated sequence of uncertainty cutoffs finding the cutoff with the lowest validation error this can be used together with continuous pruning during generation, but is particularly important for parallel generation where continuous pruning is not possible
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also fix some handling for coordination number extensions
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This adds a number of improvements to single evaluation SIDT generation:
In particular, this framework allows significant scale up in the size of datasets we can efficiently train single evaluation SIDTs on.