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Scaling Optimal Classification Trees via Adaptive Feature and Sample Reduction

This story is from 2026-09-09. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2609.05826v1 Announce Type: new Abstract: Dynamic programming for optimal classification trees becomes computationally expensive as the numbers of features and training samples increase. We develop a joint feature- and sample-space reduction framework based on STreeD. Weighted STreeD merges d…

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  1. 2026-09-09 04:00 · arXiv cs.LG
    Scaling Optimal Classification Trees via Adaptive Feature and Sample Reduction

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