title: Implementation of Gaussian Process Regression in Python y(n_samples, n_targets)
body: <p>I am working on some price data with x = day1, day2, day3,...etc. on day1, I have let's say 15 price points(y), day2, I have 30 price points(y2), and so on.</p>
  
  <p>When I read the documentation of Gaussian Process Regression: 
  <a href="http://scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.GaussianProcess.html#sklearn.gaussian_process.GaussianProcess.fit" rel="noreferrer">http://scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.GaussianProcess.html#sklearn.gaussian_process.GaussianProcess.fit</a></p>
  
  <p>y is shape (n_samples, n_targets) with the observations of the output to be predicted.</p>
  
  <p>I assume n_targets refers all the price points I observed on each day. However, the number of price points on each day are not the same. I wonder how to deal with a case like this? </p>
  
  <p>Many thanks! </p>