3 Common Modeling Mistakes In Machine Learning

It's always nice to see a model that scores highly. Unfortunately, a model that is trained based on the wrong evaluation metric is useless. It is not too uncommon for users to perform a grid search while using the default value for the scoring parameter. The default scoring metric in the grid search is accuracy, which certainly isn't ideal for many cases. For example, the accuracy metric is a poor evaluation metric for imbalanced datasets.