Tree Ensembles on the Induced Discrete Space
PulseAugur coverage of Tree Ensembles on the Induced Discrete Space — every cluster mentioning Tree Ensembles on the Induced Discrete Space across labs, papers, and developer communities, ranked by signal.
3 day(s) with sentiment data
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AI benchmark ActMOF accelerates metal-organic framework synthesis
Researchers have developed ActMOF, a new benchmark for comparing active learning strategies in the synthesis of metal-organic frameworks (MOFs). This system uses experimentally measured data from aluminum-carboxylate MO…
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New protocol improves ML evaluation for perovskite solar cells
A new protocol for evaluating machine learning models in perovskite photovoltaics has been developed to address the issue of data duplication in existing random splitting methods. This provenance-grouped protocol progre…
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Genetic programming's evolution is shaped by downstream learners
Researchers have explored how downstream learners influence the evolutionary process in genetic programming. They found that the choice of learner significantly impacts the complexity of the program that genetic program…
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Kernel of Partition Paths unifies tree ensemble representations
A new paper introduces the Kernel of Partition Paths (KPP), a novel representation for tree ensembles that unifies prediction, attribution, and robustness guarantees. KPP indexes the feature map by forest nodes, using a…
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New RuleSHAP framework enhances ML inference for epidemiological data
Researchers have developed a new framework called RuleSHAP to improve statistical inference for machine learning models in epidemiology. This framework integrates Bayesian regression, tree ensembles, and Shapley values …
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New PINE method boosts tree ensemble compression by 30%
Researchers have developed PINE, a novel pruning method for tree ensembles designed to improve compression ratios while maintaining prediction consistency within an in-distribution region. Unlike existing faithful pruni…