title: Is there a way to find arg_max() of a RandomForestRegressor?
body: <p>I'm using ML to predict a numerical output (a percentage from 0-100) from a number of (discretized) input variables. I want to find the combination of input variables that the model thinks will give the maximum output.</p>
  <p>I have a fitted <code>RandomForestRegressor</code> model in Python (3.7.10), and currently evaluate the model's predictions for every combination of input variables.</p>
  <pre><code>model = RandomForestRegressor(n_estimators ...)
  modelfit = model.fit(a, b)
  modelpredictions = model.predict(combinations)
  </code></pre>
  <p>However, this doesn't scale well with more variables/finer steps.</p>
  <p>So, is there a simpler way to extract the global optimum of the model? E.g. an equivalent to <code>argmax()</code>.</p>