2016 Winter Simulation Conference (WSC) · 2016 · 13 citations · 28 references
Gaussian process fitting, or kriging, is often used to create a model from a set of data. Many available software packages do this, but we show that very different results can be obtained from different packages even when using the same data and model. Seven different fitting packages that run on four different platforms are compared using various data functions and data sets that reveal there are stark differences between the packages. In addition to comparing the prediction accuracy, the predictive variance-which is important for evaluating precision of predictions and is often used in stopping criteria-is also evaluated.
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Scikit-learn: Machine Learning in Python
Fabián Pedregosa, Gaël Varoquaux, Alexandre Gramfort et al. · arXiv (Cornell University) · 2012 · 63.3K citations · Full text
Design and Analysis of Computer Experiments
Jerome Sacks, William J. Welch, Toby J. Mitchell et al. · Statistical Science · 1989 · 6.9K citations · Full text