Beyond prediction: Assessing stability in feature selection methods for materials science applications

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Regions with many nearby points keep subdividing. Regions with few or no points stay large. The tree adapts to the data: dense areas get fine-grained cells, sparse areas stay coarse. The split grid is predetermined (always at midpoints), but the tree only refines cells that need it. Sparse regions stay as single large nodes while dense regions subdivide deeply.,详情可参考safew官方版本下载

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