Machine Learning
高斯过程回归
Gaussian process regressionA non-parametric Bayesian approach to regression analysis that models the relationship between input variables and output variables as a distribution over functions. It provides a principled way to predict values and quantify uncertainty. / 一种用于回归分析的非参数贝叶斯方法，将输入变量与输出变量之间的关系建模为函数分布。它提供了一种预测值和量化不确定性的原则性方法。
- Knowledge type
- 数学理论
- First proposed or discovered
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- Turkey Farm member
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- 农场主
- Last updated
- 2026-10-27 18:00:59
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Main parameters and performance indicators
kernel function: defines the covariance structure between data pointsnoise level: variance of the observation noisetraining data: set of input-output pairs used to infer the function
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Related literature
ranked by community starsAgro-residue forecasting for biogas-based green rural electrification in India: A Gaussian process regression-based decision frameworkOpen source
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1 recordsRecord title: Gaussian process regression.
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