在本文中我们将以高斯过程回归(Gaussian process regression,GPR)模型为例,对MOGP最基础的几个模型,即Intrinsic coregionalization model (ICM)、Semiparametric Latent Factor Model(SLFM)和Linear model of coregionalization(LMC)分别进行介绍。 注:
参考: Dreisteine:高斯过程回归(Gaussian Process Regression) 多元正态分布的极大似然估计_Joyliness的博客-CSDN博客_多元正态分布的极大似然估计 Enzo:多输出高斯过程 (multiple output GP) marsggbo:如何理解正定矩阵和半正定矩阵 youtube.com/watch? andrewcharlesjones.github.io ...
Multi-output Gaussian processes (MOGP) are probability distributions over vector-valued functions, and have been previously used for multi-output regression and for multi-class classification. A less explored facet of the multi-output Gaussian process is that it can be used as a generative model ...
Chen, "Gaussian process regression with multiple response variables," Chemometrics and Intelligent Laboratory Systems, vol. 142, pp. 159-165, Mar. 2015.B. Wang and T. Chen, "Gaussian process regression with multiple response variables," Chemometrics and Intelligent Laboratory Systems, vol. 142, ...
Multi-output Gaussian process using a Gaussian kernel and a Gaussian covariance function This example shows how it is possible to make multiple regression over four outputs using a Gaussian process constructed with the convolution process approach. Note that there are some ranges of missing data for...
Multiple snapshot RFI localization fusion algorithm based on Gaussian process regression Yang ZhaoRong JinYinan LiHaofeng Dou
Table 3. SPSS output from standard multiple regression. Empty CellVariableCorrelationpMeanSDBSEβt Empty Cell Extraversion − 0.112 0.142 2.5457 0.40370 0.075 0.090 0.090 0.832 Empty Cell Agreeableness − 0.382 0.000 2.9809 0.38232 − 0.302 0.095 − 0.343 − 3.188 Empty Cell Openness − 0.0...
Multiple regression is a statistical technique that can be used to analyze the relationship between a single dependent variable and several independent variables. The objective of multiple regression analysis is to use the independent variables whose values are known to predict the value of the single...
In this study, we extend the spatial distribution estimation method using Gaussian Process Regression based on the superposition of multiple random fields, and propose a method that considers the correlation among them for the random component. The spatial distribution of the estimated geotechnical ...
2.2.1. Gaussian Process Regression Gaussian process regression (GPR) involves the generation of machine learning combination modeling and was used to improve the presented ensemble machine learning model. GPR was used to estimate feasibility, which generates data for the input (X) and output (Y) ...