you just put any higher value to that threshold okay or you can also cut the error so joining for addiction during the learning phase you have to write your own loss and what you do is you compute the error and for big errors you need to cap them so that your model will not will not be biased towards those predators those outliers especially if you are using some metrics like the mean squared error which encases the importance of the outliers so after trying the winterization will have a new spot that you can compare with your