<h4 dir="auto">Describe the workflow you want to enable</h4>
<p dir="auto">At the moment it is possible to use nystroem only by specifying the component number. Datapoints<br>
are then randomly chosen. I want to be able to pick my data points with other methods like K-Means++.</p>
<h4 dir="auto">Describe your proposed solution</h4>
<p dir="auto">The solution would be to enable the parameter n_components to take n-dim arrays and pandas dataframes as input.<br>
So n_components = [ ... ] with a small len(n_components) check because of the sample size.</p>
<p dir="auto">I think this is a rather small fix to enable some nice functionality You could make a comment, that the array<br>
has to be a subset of the data which nystroem is applied to.</p>
<h4 dir="auto">Describe alternatives you've considered, if relevant</h4>
<h4 dir="auto">Additional context</h4>
<p dir="auto">Dear developers,<br>
I would to ask for support for the provide specific landmarks points to approximate the Nystroem kernel approximation. In the current version of the code, the points are chosen randomly. In this case it is often more convenient for the user to select them beforehand using some method and already build the approximation using this method.</p>
<p dir="auto">Possible solution<br>
To be presented in a separate PR</p>