title: limit allowed values for polynomial with RANSACRegressor
body: <p>I have the following white pixels as input data and use sklearn.linear_model.RANSACRegressor to fit a polynomial of degree 2 (quadratic) to avoid outliers. The result in this case is shown in red and is completely correct:</p>
  
  <p><a href="https://i.stack.imgur.com/PgyaP.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/PgyaP.png" alt="enter image description here"></a></p>
  
  <p>However, I know in my application that the quadratic curve will always have its minimum/maximum on the right side of this image (but I don't know at which height) and that the curvature can't be that strong.
  To put it differently: I already know that my best fit should be like the blue line and that the other points are corrupt outliers.</p>
  
  <p>Is there a way to control or limit the outcome of RANSACRegressor by (e.g.) providing a loss function which punishes very strong curvatures but still tries to find the best fit when using lower curvatures? </p>
  
  <p>Thanks in advance for any hints or links :-)</p>