Feb. 5, 2024, 3:43 p.m. | Marcos Matabuena Juan C. Vidal Oscar Hernan Madrid Padilla Jukka-Pekka Onnela

cs.LG updates on arXiv.org arxiv.org

In this paper, we introduce a kNN-based regression method that synergizes the scalability and adaptability of traditional non-parametric kNN models with a novel variable selection technique. This method focuses on accurately estimating the conditional mean and variance of random response variables, thereby effectively characterizing conditional distributions across diverse scenarios.Our approach incorporates a robust uncertainty quantification mechanism, leveraging our prior estimation work on conditional mean and variance. The employment of kNN ensures scalable computational efficiency in predicting intervals and statistical accuracy …

adaptability algorithm automated cs.lg knn mean non-parametric novel paper parametric quantification random regression scalability stat.co stat.me stat.ml uncertainty variables variance

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