title: How can I find the value with the minimum MSE with a numpy array?
body: <p>My possible values are:</p>
  
  <pre><code>0: [0 0 0 0]
  1: [1 0 0 0]
  2: [1 1 0 0]
  3: [1 1 1 0]
  4: [1 1 1 1]
  </code></pre>
  
  <p>I have some values:</p>
  
  <pre><code>[[0.9539342  0.84090066 0.46451256 0.09715253],
   [0.9923432  0.01231235 0.19491441 0.09715253]
   ....
  </code></pre>
  
  <p>I want to figure out which of my possible values this is the closest to my new values. Ideally I want to avoid doing a <code>for</code> loop and wonder if there's some sort of vectorized way to search for the minimum mean squared error?</p>
  
  <p>I want it to return an array that looks like: <code>[2, 1 ....</code></p>