Coma704
发表于 2025-3-23 10:57:16
Synthesis Lectures on Data Mining and Knowledge Discoveryhttp://image.papertrans.cn/e/image/311371.jpg
mucous-membrane
发表于 2025-3-23 14:23:36
978-3-031-00771-2Springer Nature Switzerland AG 2010
心痛
发表于 2025-3-23 18:09:37
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VOC
发表于 2025-3-24 01:33:54
https://doi.org/10.1007/978-1-4613-0443-2 view the classic ensemble methods of Bagging, Random Forest, AdaBoost, and Gradient Boosting as special cases of a single algorithm. This unified view clarifies the properties of these methods and suggests ways to improve their accuracy and speed.
plasma
发表于 2025-3-24 05:44:11
Importance Sampling and the Classic Ensemble Methods, view the classic ensemble methods of Bagging, Random Forest, AdaBoost, and Gradient Boosting as special cases of a single algorithm. This unified view clarifies the properties of these methods and suggests ways to improve their accuracy and speed.
AUGUR
发表于 2025-3-24 07:21:48
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Ventilator
发表于 2025-3-24 12:04:42
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Dissonance
发表于 2025-3-24 17:04:23
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似少年
发表于 2025-3-24 20:21:25
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craven
发表于 2025-3-24 23:29:37
The Science and Engineering of Materialsng complexity according to a model’s behavior rather than its appearance, the utility of Occam’s Razor is restored. We’ll demonstrate this on a two-dimensional decision tree example where the whole (an ensemble of trees) has less GDF complexity than any of its parts.