There are a number of parameters that we need to tune or be aware of:
- Max_depth: One of the most important parameters is max_depth. It captures the essence of how deep the tree can get. More depth in the tree means that it is able to extract more information from the features. However, sometimes, excessive depth might be a cause of worry as it tends to bring along overfitting as well.
- min_samples_split: This represents the minimum number of samples required to split an internal node. This can vary between considering at least one sample at each node to considering all of the samples at each node. When we increase this parameter, the tree becomes more constrained as it has to consider more samples at each node. ...