擅长:python、mysql、java
<p>是的,你绝对可以在<code>scikit_learn</code>中完成。</p>
<p>实际上,可以使用各向异性协方差核是kriging/Gaussian过程回归的一个基本特征。</p>
<p>由于它在<a href="http://scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.GaussianProcess.html" rel="noreferrer">manual</a>(下面引用)中被精确化,所以您可以自己设置协方差的参数,也可以估计它们。你可以选择所有参数都相等或者都不同。</p>
<blockquote>
<p>theta0 : double array_like, optional
An array with shape (n_features, ) or (1, ). The parameters in the
autocorrelation model. If thetaL and thetaU are also specified, theta0
is considered as the starting point for the maximum likelihood
estimation of the best set of parameters. Default assumes isotropic
autocorrelation model with theta0 = 1e-1.</p>
</blockquote>