title: What is random_state parameter in scikit-learn TSNE?
body: <p>According to <a href="http://scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html" rel="nofollow noreferrer">http://scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html</a> random_state is </p>
  
  <blockquote>
    <p>random_state : int or RandomState instance or None (default) Pseudo
    Random Number generator seed control. If None, use the numpy.random
    singleton. Note that different initializations might result in
    different local minima of the cost function.</p>
  </blockquote>
  
  <p>What state is being seeded ? How does this affect the tsne implementation ? This parameter is not mentioned in tsne paper : <a href="http://jmlr.csail.mit.edu/papers/volume9/vandermaaten08a/vandermaaten08a.pdf" rel="nofollow noreferrer">http://jmlr.csail.mit.edu/papers/volume9/vandermaaten08a/vandermaaten08a.pdf</a></p>
  
  <p>Update 1 : </p>
  
  <p>While <a href="https://stackoverflow.com/questions/42476032/classification-results-depend-on-random-state">Classification results depend on random_state?</a> certainly helps to explain why random state is used in sklearn it does not clarify how random state is used in sklearn tsne algorithm implementation.</p>