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.
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The converter supports all model types via the --model flag:。关于这个话题，同城约会提供了深入分析
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