I am running Spark MLLib's Decisioin Tree model. While parameter tuning, I came across the minInstancesPerNode but I am not sure of the implications of setting it too low or too high. Can anyone help me understand its purpose and importance?
As per my understanding, it would be overfitting if there are very few instances in a node, since the tree would be too granular. I wanted to get more clarity.